https://www.spreaker.com/podcast/sheryians-ai-school--7315562esLeisureCopyright ferthttps://d3wo5wojvuv7l.cloudfront.net/t_rss_itunes_square_1400/images.spreaker.com/original/ba33512135435e69074624ae5d651ad9.jpghttps://www.spreaker.com/podcast/sheryians-ai-school--7315562Fri, 04 Sep 2026 01:14:51 +0000fertfertfeeds@spreaker.comWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python and everything smart enough to shape the future Here we simplify complex topics, share real-world...falsea04c1ad0-6797-52c6-8bbb-b86dad05e100episodichttps://www.spreaker.com/episode/graph-neural-networks-for-research-topic-classification--74883247Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

Instructor in this video
Tanishq Vyas

In this video, we build an end-to-end Research Topic Classification project using Graph Convolutional Networks (GCN) with PyTorch. We work with graph-based data, train a GCN model to classify research topics, convert the trained model using ONNX, and deploy it for real-world inference.

Code Files
https://github.com/tanishq-latent/CORA-Project

Data Analytics Course
https://www.sheryians.com/courses/6a6…

Data Science Course
https://www.sheryians.com/courses/68d…

Discord
https://discord.gg/7R5eJT99B

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, GraphNeuralNetworks, GCN, PyTorch, ONNX, DeepLearning, AIProjects, MLProjects, AIForBeginners, MLForBeginners, DataScienceCareer]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306214Mon, 31 Aug 2026 14:34:37 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. Instructor in this video Tanishq Vyas In this video,...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

Instructor in this video
Tanishq Vyas

In this video, we build an end-to-end Research Topic Classification project using Graph Convolutional Networks (GCN) with PyTorch. We work with graph-based data, train a GCN model to classify research topics, convert the trained model using ONNX, and deploy it for real-world inference.

Code Files
https://github.com/tanishq-latent/CORA-Project

Data Analytics Course
https://www.sheryians.com/courses/6a6…

Data Science Course
https://www.sheryians.com/courses/68d…

Discord
https://discord.gg/7R5eJT99B

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, GraphNeuralNetworks, GCN, PyTorch, ONNX, DeepLearning, AIProjects, MLProjects, AIForBeginners, MLForBeginners, DataScienceCareer]]>18616falsefullhttps://www.spreaker.com/episode/build-an-end-to-end-nlp-project-with-deep-learning-fastapi-deployment--74883259Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

code files - https://github.com/tanishq-latent/Emotion-Prediction

Data analytics course - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda

Data Science Course - https://www.sheryians.com/courses/68da779296b89547293c7a26

Discord link - https://discord.gg/ewgPctaar

In this 6-hour complete project, we build a real-world NLP application from scratch using Deep Learning, FastAPI, and Render. Along the way, we understand the concepts, build the project, create the API, and deploy it live.

Perfect for anyone looking to learn how an AI/ML project actually goes from idea to deployment.

Instructor in this video - Tanishq vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz


SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306183Mon, 10 Aug 2026 14:32:37 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. code files -...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

code files - https://github.com/tanishq-latent/Emotion-Prediction

Data analytics course - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda

Data Science Course - https://www.sheryians.com/courses/68da779296b89547293c7a26

Discord link - https://discord.gg/ewgPctaar

In this 6-hour complete project, we build a real-world NLP application from scratch using Deep Learning, FastAPI, and Render. Along the way, we understand the concepts, build the project, create the API, and deploy it live.

Perfect for anyone looking to learn how an AI/ML project actually goes from idea to deployment.

Instructor in this video - Tanishq vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz


SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>17638falsefullhttps://www.spreaker.com/episode/lets-have-a-talk--74883277discord link - https://discord.gg/m6FYWWAQps
Data analytics course - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306189Tue, 04 Aug 2026 17:41:10 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! discord link - https://discord.gg/m6FYWWAQps Data analytics course - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda Hey everyone! I’m going LIVE to answer all your doubts about...discord link - https://discord.gg/m6FYWWAQps
Data analytics course - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept this is your chance to ask your questions LIVE and get them solved instantly.]]>3731falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-course-talk--74883264course link - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306178Sat, 01 Aug 2026 17:33:07 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! course link - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep...course link - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>3246falsefullhttps://www.spreaker.com/episode/complete-data-analytics-course-launch--74883272
Change your future in next 6 months - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda

In this video I'm introducing the new Data Analytics course I've built. The course goes live on 7 August, and registration is open now.

This is one of the rare fields in India where nobody asks about your degree. Tech, Commerce, Arts, the entry route is the same for everyone. You just need to know the route.

What's inside the course:
Python, NumPy, Pandas, Matplotlib, Seaborn, SQL, Excel, Power BI, Machine Learning, and real business case studies on datasets like Zomato, Blinkit, Amazon and Starbucks.

Plus live mentor sessions, project building, and a community where you learn alongside other students.

Early bird: Special bonus for the first 100 registrations. Apply coupon code DIFFERENT to get it at ₹3999, and the price goes up ₹250 every week after that.

Registration link is below. Tomorrow's video breaks down the full curriculum in detail.

🎓 speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz

🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306209Sat, 01 Aug 2026 14:30:14 +0000fertWelcome to Sheryians AI School Change your future in next 6 months - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda In this video I'm introducing the new Data Analytics course I've built. The course goes live on 7 August, and...
Change your future in next 6 months - https://www.sheryians.com/courses/6a61c40df87dceea1fa43bda

In this video I'm introducing the new Data Analytics course I've built. The course goes live on 7 August, and registration is open now.

This is one of the rare fields in India where nobody asks about your degree. Tech, Commerce, Arts, the entry route is the same for everyone. You just need to know the route.

What's inside the course:
Python, NumPy, Pandas, Matplotlib, Seaborn, SQL, Excel, Power BI, Machine Learning, and real business case studies on datasets like Zomato, Blinkit, Amazon and Starbucks.

Plus live mentor sessions, project building, and a community where you learn alongside other students.

Early bird: Special bonus for the first 100 registrations. Apply coupon code DIFFERENT to get it at ₹3999, and the price goes up ₹250 every week after that.

Registration link is below. Tomorrow's video breaks down the full curriculum in detail.

🎓 speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz

🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>477falsefullhttps://www.spreaker.com/episode/ml-project-classifying-nyc-house-types-from-scratch--74883294Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

🎓 Instructor in this video - Tanishq vyas

code files - https://github.com/tanishq-latent/NYC-Airbnb-Room-Type-Predictor

In this video, I built a Machine Learning model that classifies house types in New York City
We go through the entire pipeline, from raw data to a live deployed app.

What's covered:
✅ Data Cleaning & Preprocessing
✅ Exploratory Data Analysis (EDA)
✅ Feature Engineering
✅ Model Training & Evaluation
✅ Deployment on Render


❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306208Tue, 28 Jul 2026 14:30:33 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. 🎓 Instructor in this video - Tanishq vyas code files...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

🎓 Instructor in this video - Tanishq vyas

code files - https://github.com/tanishq-latent/NYC-Airbnb-Room-Type-Predictor

In this video, I built a Machine Learning model that classifies house types in New York City
We go through the entire pipeline, from raw data to a live deployed app.

What's covered:
✅ Data Cleaning & Preprocessing
✅ Exploratory Data Analysis (EDA)
✅ Feature Engineering
✅ Model Training & Evaluation
✅ Deployment on Render


❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>10431falsefullhttps://www.spreaker.com/episode/sheryians-ai-sunday-live-qna--74883261
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306199Sun, 26 Jul 2026 18:25:44 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>4039falsefullhttps://www.spreaker.com/episode/building-deploying-a-mental-health-score-predictor-full-ml-project--74883289Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

In this video, I built and deployed a Machine Learning model that predicts a person's Mental Health Score based on lifestyle and behavioral data. From data cleaning and model training to building a fully working deployed app this video covers the complete end-to-end ML project.

course link - https://sheryians.com/courses/68da779296b89547293c7a26

code files - https://github.com/tanishq-latent/Mental-Health-Score

Instructor in this video - Tanishq vyas



❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306223Wed, 22 Jul 2026 14:30:02 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. In this video, I built and deployed a Machine...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

In this video, I built and deployed a Machine Learning model that predicts a person's Mental Health Score based on lifestyle and behavioral data. From data cleaning and model training to building a fully working deployed app this video covers the complete end-to-end ML project.

course link - https://sheryians.com/courses/68da779296b89547293c7a26

code files - https://github.com/tanishq-latent/Mental-Health-Score

Instructor in this video - Tanishq vyas



❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>15162falsefullhttps://www.spreaker.com/episode/git-github-full-course-for-beginners-industry-workflow-part-2--74883275Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

🎓 Instructor in this video - Dhanesh Malviya

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306225Mon, 20 Jul 2026 14:30:24 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. 🎓 Instructor in this video - Dhanesh Malviya ❤️...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

🎓 Instructor in this video - Dhanesh Malviya

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>4103falsefullhttps://www.spreaker.com/episode/best-entry-level-ai-jobs-for-freshers-ranked-easy-to-hard--74883248Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.
Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306200Fri, 17 Jul 2026 14:00:18 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. Speaker in this video - Akarsh Vyas ❤️ Support the...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.
Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>1032falsefullhttps://www.spreaker.com/episode/machine-learning-projects-that-actually-get-you-hired--74883273Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.
In this video, I break down the exact projects I'd build if I were a student today trying to actually get placed not projects that just sit in a Jupyter notebook, but ones that prove you can think like a data scientist and ship like an engineer.

Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306182Wed, 15 Jul 2026 14:00:13 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. In this video, I break down the exact projects I'd...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.
In this video, I break down the exact projects I'd build if I were a student today trying to actually get placed not projects that just sit in a Jupyter notebook, but ones that prove you can think like a data scientist and ship like an engineer.

Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>922falsefullhttps://www.spreaker.com/episode/ai-engineer-roadmap-2026-90-of-students-get-this-wrong--74883265
Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

In this video, I break down the EXACT 4-step roadmap I'd follow if I were starting from scratch today to become an AI Engineer — not a prompt engineer, not an ML engineer, an actual AI Engineer who builds real, production-ready AI products.
Most students confuse AI Engineering with Machine Learning Engineering. They're NOT the same. An ML Engineer builds the engine (trains models). An AI Engineer builds the car around it (uses existing models like GPT-4o/Claude to build real products — RAG systems, agents, AI apps).
🎓 speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306190Thu, 09 Jul 2026 15:07:53 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. In this video, I break down the EXACT 4-step roadmap...
Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

In this video, I break down the EXACT 4-step roadmap I'd follow if I were starting from scratch today to become an AI Engineer — not a prompt engineer, not an ML engineer, an actual AI Engineer who builds real, production-ready AI products.
Most students confuse AI Engineering with Machine Learning Engineering. They're NOT the same. An ML Engineer builds the engine (trains models). An AI Engineer builds the car around it (uses existing models like GPT-4o/Claude to build real products — RAG systems, agents, AI apps).
🎓 speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>1117falsefullhttps://www.spreaker.com/episode/how-i-would-become-a-machine-learning-engineer-in-2026-if-i-started-today--74883283Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

speaker in this video - Akarsh Vyas

Everyone thinks "Machine Learning Engineer" = do a course, learn some ML, get placed. Wrong.
In this video, I break down the EXACT 4-step roadmap I'd follow if I were starting from scratch today to become an ML Engineer not just to learn ML, but to actually get hired as one.
Most students stop at Step 2 (courses + notebooks) and wonder why they're not getting interview calls. The real separation between "ML student" and "ML Engineer" happens in Steps 3 and 4 and almost nobody talks about it.
Here's what I cover:
✅ Step 1: The foundation everyone skips (and pays for later)
✅ Step 2: Why 5 courses + 0 projects = 0 offers
✅ Step 3: The engineering skills that actually separate you from the crowd
✅ Step 4: Building a portfolio that gets you noticed, not ignored
Plus the interview round almost no one prepares for (ML System Design), and why explaining YOUR OWN project matters more than the code itself.


❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306191Wed, 08 Jul 2026 14:00:23 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. speaker in this video - Akarsh Vyas Everyone thinks...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

speaker in this video - Akarsh Vyas

Everyone thinks "Machine Learning Engineer" = do a course, learn some ML, get placed. Wrong.
In this video, I break down the EXACT 4-step roadmap I'd follow if I were starting from scratch today to become an ML Engineer not just to learn ML, but to actually get hired as one.
Most students stop at Step 2 (courses + notebooks) and wonder why they're not getting interview calls. The real separation between "ML student" and "ML Engineer" happens in Steps 3 and 4 and almost nobody talks about it.
Here's what I cover:
✅ Step 1: The foundation everyone skips (and pays for later)
✅ Step 2: Why 5 courses + 0 projects = 0 offers
✅ Step 3: The engineering skills that actually separate you from the crowd
✅ Step 4: Building a portfolio that gets you noticed, not ignored
Plus the interview round almost no one prepares for (ML System Design), and why explaining YOUR OWN project matters more than the code itself.


❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>1082falsefullhttps://www.spreaker.com/episode/pydantic-full-course-2026-data-validation-for-python-ai-developers--74883291Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

🎓 Instructor in this video
Tanishq Vyas

Pydantic is the one library every Python and AI developer eventually needs — from validating FastAPI requests to structuring LLM outputs in LangChain and LangGraph. In this course, you'll learn Pydantic from scratch: models, validators, field types, nested schemas, and the real use cases you'll actually hit on the job.
No theory-only lectures practical, project-driven Pydantic, taught the way it's actually used in production and in modern AI pipelines.
By the end, you'll know exactly how to validate, structure, and trust the data flowing through your applications.

Code Files - https://github.com/tanishq-latent/Pydantic

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306188Tue, 07 Jul 2026 14:30:33 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. 🎓 Instructor in this video Tanishq Vyas Pydantic is...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

🎓 Instructor in this video
Tanishq Vyas

Pydantic is the one library every Python and AI developer eventually needs — from validating FastAPI requests to structuring LLM outputs in LangChain and LangGraph. In this course, you'll learn Pydantic from scratch: models, validators, field types, nested schemas, and the real use cases you'll actually hit on the job.
No theory-only lectures practical, project-driven Pydantic, taught the way it's actually used in production and in modern AI pipelines.
By the end, you'll know exactly how to validate, structure, and trust the data flowing through your applications.

Code Files - https://github.com/tanishq-latent/Pydantic

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>4615falsefullhttps://www.spreaker.com/episode/complete-agentic-ai-course-with-langgraph--74883255Learn Agentic AI from scratch by building real projects using LangGraph — the framework used to create and orchestrate production-grade AI agents.
In this single video, you'll master the 5 core workflow types that power every modern AI agent, and by the end you'll be able to build your own multi-agent systems, RAG-powered chatbots, and human-in-the-loop applications.
🔹 What you'll learn
✔️ Generative AI vs Agentic AI — the real difference
✔️ LangGraph fundamentals — state, nodes, edges, conditional edges
✔️ Sequential workflows — your first LangGraph project
✔️ Parallel workflows — reducers and fan-out/fan-in
✔️ Conditional workflows — building a RAG-based college assistant
✔️ Iterative workflows — self-reviewing LinkedIn post generator with tools
✔️ Human-in-the-Loop — pausing agents for human approval

🔹 Projects you'll build
✅ Content pipeline (Sequential)
✅ Multi-source research agent (Parallel)
✅ College RAG chatbot with 2 PDFs (Conditional)
✅ LinkedIn Post Generator with self-review loop (Iterative)
✅ HITL LinkedIn Generator with human approval (Human-in-the-Loop)

🔹 Prerequisites
* Intermediate Python
* Basic LangChain knowledge
* An OpenAI or Groq API key

🔹 Timestamps
00:00:00 - 00:01:51 - Introduction
00:01:51 - 00:16:09 - Generative Ai vs Agentic Al
00:16:09 - 00:28:39 - Why Langgraph
00:28:39 - 01:27:26 - Sequential workflow and lang graph basics
01:27:26 - 02:02:10 - Parallel workflow and reducers
02:02:10 - 03:21:30 - Conditional workflow and RAG implementation
03:21:30 - 04:56:35 - Iterative workflow and project
04:56:35 - 05:18:07 - Human in the loop workflow




🔹 GitHub Repositoryhttps://github.com/AkarshVyas/Agentic-AI-youtube

🔹 Resources & LinksMy notes - https://slides.com/sheryianscodingschool/bento

Tavily (Free API): https://tavily.comGroq (Free API): https://console.groq.com

🔹 Related VideosLangChain Full Course: https://www.youtube.com/playlistlist=PLaldQ9PzZd9oXR4PMGR4pr_DX4wFHkFwR

If this video helped you, please like, share, and subscribe. It genuinely helps the channel grow.
Drop a comment with what you want me to cover next — MLOps? Deployment with FastAPI? Multi-agent systems? Let me know.

#AgenticAI #LangGraph #AIAgents #LangChain #GenerativeAI #MachineLearning #Python #AIDevelopment]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306184Fri, 03 Jul 2026 14:30:39 +0000fertAgentic AI Crash Course | Build Real AI Agents with LangGraph (Complete Course in One Video) Learn Agentic AI from scratch by building real projects using LangGraph — the framework used to create and orchestrate production-grade AI agents. In this...Learn Agentic AI from scratch by building real projects using LangGraph — the framework used to create and orchestrate production-grade AI agents.
In this single video, you'll master the 5 core workflow types that power every modern AI agent, and by the end you'll be able to build your own multi-agent systems, RAG-powered chatbots, and human-in-the-loop applications.
🔹 What you'll learn
✔️ Generative AI vs Agentic AI — the real difference
✔️ LangGraph fundamentals — state, nodes, edges, conditional edges
✔️ Sequential workflows — your first LangGraph project
✔️ Parallel workflows — reducers and fan-out/fan-in
✔️ Conditional workflows — building a RAG-based college assistant
✔️ Iterative workflows — self-reviewing LinkedIn post generator with tools
✔️ Human-in-the-Loop — pausing agents for human approval

🔹 Projects you'll build
✅ Content pipeline (Sequential)
✅ Multi-source research agent (Parallel)
✅ College RAG chatbot with 2 PDFs (Conditional)
✅ LinkedIn Post Generator with self-review loop (Iterative)
✅ HITL LinkedIn Generator with human approval (Human-in-the-Loop)

🔹 Prerequisites
* Intermediate Python
* Basic LangChain knowledge
* An OpenAI or Groq API key

🔹 Timestamps
00:00:00 - 00:01:51 - Introduction
00:01:51 - 00:16:09 - Generative Ai vs Agentic Al
00:16:09 - 00:28:39 - Why Langgraph
00:28:39 - 01:27:26 - Sequential workflow and lang graph basics
01:27:26 - 02:02:10 - Parallel workflow and reducers
02:02:10 - 03:21:30 - Conditional workflow and RAG implementation
03:21:30 - 04:56:35 - Iterative workflow and project
04:56:35 - 05:18:07 - Human in the loop workflow




🔹 GitHub Repositoryhttps://github.com/AkarshVyas/Agentic-AI-youtube

🔹 Resources & LinksMy notes - https://slides.com/sheryianscodingschool/bento

Tavily (Free API): https://tavily.comGroq (Free API): https://console.groq.com

🔹 Related VideosLangChain Full Course: https://www.youtube.com/playlistlist=PLaldQ9PzZd9oXR4PMGR4pr_DX4wFHkFwR

If this video helped you, please like, share, and subscribe. It genuinely helps the channel grow.
Drop a comment with what you want me to cover next — MLOps? Deployment with FastAPI? Multi-agent systems? Let me know.

#AgenticAI #LangGraph #AIAgents #LangChain #GenerativeAI #MachineLearning #Python #AIDevelopment]]>19084falsefullhttps://www.spreaker.com/episode/git-github-full-course-for-beginners-industry-workflow-part-1--74883278
In this video, we dive into the fundamentals of Git and GitHub, the most widely used version control tools in modern software development. You'll learn how to create repositories, track file changes, stage and commit code, manage branches, merge changes, and connect your local projects with GitHub.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

File Link - https://app.notion.com/p/Git-GitHub-Command-Reference-37b0ec11c39c8021a759feae4417df22?source=copy_link

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/
🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

#Git , #GitHub , #VersionControl , #Developer , #Programming , #Coding , #WebDevelopment , #SoftwareEngineering , #LearnToCode , #SheryiansAISchool]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306221Wed, 10 Jun 2026 14:00:12 +0000fertMaster Git & GitHub from Scratch | Version Control Explained | Part 1 In this video, we dive into the fundamentals of Git and GitHub, the most widely used version control tools in modern software development. You'll learn how to create...
In this video, we dive into the fundamentals of Git and GitHub, the most widely used version control tools in modern software development. You'll learn how to create repositories, track file changes, stage and commit code, manage branches, merge changes, and connect your local projects with GitHub.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

File Link - https://app.notion.com/p/Git-GitHub-Command-Reference-37b0ec11c39c8021a759feae4417df22?source=copy_link

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/
🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

#Git , #GitHub , #VersionControl , #Developer , #Programming , #Coding , #WebDevelopment , #SoftwareEngineering , #LearnToCode , #SheryiansAISchool]]>3965falsefullhttps://www.spreaker.com/episode/100k-live-sheryians-ai-school--74883269
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306194Tue, 02 Jun 2026 18:08:28 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>3481falsefullhttps://www.spreaker.com/episode/the-exact-path-i-would-follow-to-become-a-data-analyst-in-2026--74883268
Most people who start learning Data Analytics have no idea where to begin. They jump from course to course, learn 5 tools at once, watch tutorials for months and build nothing and then wonder why they are not getting hired.
In this video I am going to tell you exactly how I would learn Data Analytics if I were starting from zero today. Not a vague roadmap. Not a list of courses. The exact path what to learn first, what to learn next, how many projects to build, what skills Indian companies actually test in interviews, and the one mistake that is silently killing most fresher's chances before they even apply.
This is the roadmap I wish someone had given me on day one. If you are a first year student, a second year student, or someone who has been trying to get into Data Analytics and feeling stuck this video is made for you.


Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306206Fri, 29 May 2026 15:00:07 +0000fertWelcome to Sheryians AI School Most people who start learning Data Analytics have no idea where to begin. They jump from course to course, learn 5 tools at once, watch tutorials for months and build nothing and then wonder why they are not getting...
Most people who start learning Data Analytics have no idea where to begin. They jump from course to course, learn 5 tools at once, watch tutorials for months and build nothing and then wonder why they are not getting hired.
In this video I am going to tell you exactly how I would learn Data Analytics if I were starting from zero today. Not a vague roadmap. Not a list of courses. The exact path what to learn first, what to learn next, how many projects to build, what skills Indian companies actually test in interviews, and the one mistake that is silently killing most fresher's chances before they even apply.
This is the roadmap I wish someone had given me on day one. If you are a first year student, a second year student, or someone who has been trying to get into Data Analytics and feeling stuck this video is made for you.


Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>1053falsefullhttps://www.spreaker.com/episode/the-data-science-job-market-is-not-what-you-think--74883296Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306207Thu, 28 May 2026 15:39:37 +0000fertWelcome to Sheryians AI School Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future. Speaker in this video - Akarsh Vyas ❤️ Support the...Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

Speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>817falsefullhttps://www.spreaker.com/episode/ai-ml-jobs-nobody-tells-you-about-full-list-for-freshers--74883281
Every year, thousands of students enter CSE, IT, and Data Science and almost all of them think there are only two jobs in AI and ML. Data Scientist. ML Engineer. That's it.
But the reality is completely different. There are roles you have never heard of that pay more, have less competition, and are a much better fit for where you are right now as a fresher. In this video, I am breaking down every single real job title that exists in AI and ML right now from entry level roles that require zero experience, to mid level roles that are actively hiring, to brand new job titles that did not even exist 3 years ago. By the end of this video you will know exactly where you fit, what skills you need, and which role you should be targeting based on your current level. This is the video I wish someone made when I was starting out.


Speaker - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306179Wed, 27 May 2026 14:29:43 +0000fertWelcome to Sheryians AI School Every year, thousands of students enter CSE, IT, and Data Science and almost all of them think there are only two jobs in AI and ML. Data Scientist. ML Engineer. That's it. But the reality is completely different....
Every year, thousands of students enter CSE, IT, and Data Science and almost all of them think there are only two jobs in AI and ML. Data Scientist. ML Engineer. That's it.
But the reality is completely different. There are roles you have never heard of that pay more, have less competition, and are a much better fit for where you are right now as a fresher. In this video, I am breaking down every single real job title that exists in AI and ML right now from entry level roles that require zero experience, to mid level roles that are actively hiring, to brand new job titles that did not even exist 3 years ago. By the end of this video you will know exactly where you fit, what skills you need, and which role you should be targeting based on your current level. This is the video I wish someone made when I was starting out.


Speaker - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>1156falsefullhttps://www.spreaker.com/episode/before-you-start-ai-ml-watch-this-video-first--74883282
Before starting AI and ML, most students make the same mistakes — they jump into courses without a clear goal, spend months on maths before writing a single li…
Before starting AI and ML, most students make the same mistakes — they jump into courses without a clear goal, spend months on maths before writing a single line of code, switch between 10 different resources and build nothing, and keep waiting for their project to be "perfect" before sharing it. In this video, I am breaking down the 5 most important things you should know before you even open your first ML course — so you can skip the confusion, save months of wasted time, and actually start building things that matter.

🎓 speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306215Tue, 26 May 2026 15:55:24 +0000fertWelcome to Sheryians AI School Before starting AI and ML, most students make the same mistakes — they jump into courses without a clear goal, spend months on maths before writing a single li… Before starting AI and ML, most students make the same...
Before starting AI and ML, most students make the same mistakes — they jump into courses without a clear goal, spend months on maths before writing a single li…
Before starting AI and ML, most students make the same mistakes — they jump into courses without a clear goal, spend months on maths before writing a single line of code, switch between 10 different resources and build nothing, and keep waiting for their project to be "perfect" before sharing it. In this video, I am breaking down the 5 most important things you should know before you even open your first ML course — so you can skip the confusion, save months of wasted time, and actually start building things that matter.

🎓 speaker in this video - Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>508falsefullhttps://www.spreaker.com/episode/is-traditional-machine-learning-dead--74883288
In this video, we’ll break down one of the biggest debates happening in the AI industry right now —
“Is Traditional Machine Learning still worth learning in 2026?”

With the rise of Generative AI, ChatGPT, AI APIs, and LLM-based products, many students believe Machine Learning is becoming useless. But is that actually true?

This video is specially for students confused between:
Machine Learning, Deep Learning, Generative AI, LLMs, AI Engineering, and traditional AI careers.

👨‍🏫 Speaker – Akarsh Vyas

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

#machinelearning #generativeai #ai #chatgpt #llm #datascience #deeplearning #artificialintelligence #ml #genai #openai #python #aiengineering #sheryiansaischool #akarshvyas #machinelearningengineer #futureofai]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306224Mon, 25 May 2026 14:55:00 +0000fertTraditional Machine Learning is DEAD because of Generative AI? 🤖📉 In this video, we’ll break down one of the biggest debates happening in the AI industry right now — “Is Traditional Machine Learning still worth learning in 2026?” With the rise of...
In this video, we’ll break down one of the biggest debates happening in the AI industry right now —
“Is Traditional Machine Learning still worth learning in 2026?”

With the rise of Generative AI, ChatGPT, AI APIs, and LLM-based products, many students believe Machine Learning is becoming useless. But is that actually true?

This video is specially for students confused between:
Machine Learning, Deep Learning, Generative AI, LLMs, AI Engineering, and traditional AI careers.

👨‍🏫 Speaker – Akarsh Vyas

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

#machinelearning #generativeai #ai #chatgpt #llm #datascience #deeplearning #artificialintelligence #ml #genai #openai #python #aiengineering #sheryiansaischool #akarshvyas #machinelearningengineer #futureofai]]>746falsefullhttps://www.spreaker.com/episode/the-complete-mlops-ecosystem-git-docker-kubernetes-and-mlflow--74883279
Many beginners think building a Machine Learning model is the final step. But in reality, training the model is only a small part of the process. The real challenge starts when companies like Netflix, Amazon, Uber, or large startups need to deploy that model for millions of users every day.

In this session, we explain the complete MLOps pipeline used in the industry — from version control and experiment tracking to deployment, scaling, monitoring, and model drift detection.
If you are learning Machine Learning, Data Science, AI Engineering, or planning a career in production-level ML systems, this video will help you understand what companies actually do beyond model training.

👨‍🏫 Speaker – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

📚 What You Will Learn in This Video
• MLOps basics
• Why deployment matters
• Git & DVC
• MLflow & Model Registry
• FastAPI deployment
• Docker & Cloud
• Kubernetes scaling
• CI/CD automation
• Monitoring & Model Drift

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI, Machine Learning, Data Science, and Tech content, and COMMENT 💬 your thoughts below!

mlops tutorial, mlops roadmap 2026, what is mlops, machine learning deployment, mlops complete guide, mlflow tutorial, dvc tutorial, docker for machine learning, kubernetes mlops, fastapi ml model deployment, ci cd for ml, model drift explained, production machine learning, ml engineering roadmap, mlops for beginners]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306192Mon, 18 May 2026 13:30:34 +0000fertIn this video, we break down MLOps from scratch and explain how Machine Learning models actually move from training to production in real companies. Many beginners think building a Machine Learning model is the final step. But in reality, training...
Many beginners think building a Machine Learning model is the final step. But in reality, training the model is only a small part of the process. The real challenge starts when companies like Netflix, Amazon, Uber, or large startups need to deploy that model for millions of users every day.

In this session, we explain the complete MLOps pipeline used in the industry — from version control and experiment tracking to deployment, scaling, monitoring, and model drift detection.
If you are learning Machine Learning, Data Science, AI Engineering, or planning a career in production-level ML systems, this video will help you understand what companies actually do beyond model training.

👨‍🏫 Speaker – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

📚 What You Will Learn in This Video
• MLOps basics
• Why deployment matters
• Git & DVC
• MLflow & Model Registry
• FastAPI deployment
• Docker & Cloud
• Kubernetes scaling
• CI/CD automation
• Monitoring & Model Drift

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI, Machine Learning, Data Science, and Tech content, and COMMENT 💬 your thoughts below!

mlops tutorial, mlops roadmap 2026, what is mlops, machine learning deployment, mlops complete guide, mlflow tutorial, dvc tutorial, docker for machine learning, kubernetes mlops, fastapi ml model deployment, ci cd for ml, model drift explained, production machine learning, ml engineering roadmap, mlops for beginners]]>433falsefullhttps://www.spreaker.com/episode/can-you-really-learn-dsa-with-python--74883292
In this video, we’ll understand how Python can be one of the best languages to start your DSA journey. From clean syntax to faster problem solving, you’ll see why thousands of students prefer Python for Data Structures & Algorithms preparation.

Whether you’re a beginner starting coding for the first time or preparing for placements, this session will help you understand how to approach DSA the smart way using Python.

👨‍🏫 Speaker – Akarsh Vyas

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

#python #dsa #pythonfordsa #datastructures #algorithms #coding #programming #leetcode #placements #pythonprogramming #dsausingpython #softwareengineer #sheryiansaischool]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306219Sat, 16 May 2026 14:00:24 +0000fertCan You Really Learn DSA With Python? 🤔🐍 In this video, we’ll understand how Python can be one of the best languages to start your DSA journey. From clean syntax to faster problem solving, you’ll see why thousands of students prefer Python for Data...
In this video, we’ll understand how Python can be one of the best languages to start your DSA journey. From clean syntax to faster problem solving, you’ll see why thousands of students prefer Python for Data Structures & Algorithms preparation.

Whether you’re a beginner starting coding for the first time or preparing for placements, this session will help you understand how to approach DSA the smart way using Python.

👨‍🏫 Speaker – Akarsh Vyas

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

#python #dsa #pythonfordsa #datastructures #algorithms #coding #programming #leetcode #placements #pythonprogramming #dsausingpython #softwareengineer #sheryiansaischool]]>938falsefullhttps://www.spreaker.com/episode/complete-dax-tutorial-for-beginners-to-advanced-power-bi-full-course--74883334In this full-length tutorial, you’ll learn how real business calculations work inside Power BI using measures, CALCULATE, filter context, time intelligence, KPIs, and advanced DAX concepts used by data analysts in production dashboards.

Whether you're preparing for data analyst roles, improving Power BI skills, or building real dashboards — this video will give you a strong DAX foundation.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

Dataset link - https://drive.google.com/drive/folders/1qKLoBe-Na5ZAbmiNleqSBmYh33UCKybX?usp=sharing

📘 Notes Link:
https://www.notion.so/PowerBI-DAX-Playbook-35d0ec11c39c8074b29ad023a8f0f4b8?source=copy_link

⏱️ Timestamps-
00:00:00 - 00:07:22 — Intro
00:07:22 - 00:43:27 — Module Overview
Module 1
00:43:27 - 01:30:32 — Aggregation Functions
01:33:32 - 01:50:52 — Logical Functions
01:56:52 - 02:25:47 — Text Functions
02:26:47 - 02:57:19 — Project Implementation
03:02:19 - 03:04:08 — Outro
Module 2
03:04:00 - 03:05:39 — Introduction
03:05:39 - 03:20:43 — Filter Context Deep Dive
03:20:51 - 03:55:54 — CALCULATE Function Explained
03:58:55 - 04:35:17 — Filter Functions Deep Dive
05:33:17 - 05:09:59 — Iterative Functions & Best Practices
05:09:59 - 05:35:30 — Real-World Project Implementation
05:35:30 - 05:37:18 — Outro & Summary
Module 3
05:37:00 - 05:43:39 — Introduction
05:43:39 - 06:27:43 — Time Intelligence Functions
06:27:51 - 06:58:54 — Comparison & Growth Time Calculations
06:58:55 - 07:22:17 — Project Using Time Intelligence Functions
07:22:17 - 07:23:59 — Outro & Summary
Module 4
07:24:00 - 07:45:39 — Introduction to Data Modeling
07:45:39 - 08:45:43 — Practical Implementation & Project
08:45:43 - 08:46:30 — Outro & Summary
Module 5
08:46:40 - 08:50:32 — Introduction to Advanced DAX
08:50:32 - 09:11:52 — Rank Functions
09:11:52 - 09:26:47 — Table Functions
09:26:47 - 09:44:19 — More DAX Functions
09:44:19 - 09:45:05 — Practice Project & Summary

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

Power BI, DAX, Power BI Tutorial, Data Analytics, Business Intelligence, DAX Tutorial, Power BI Full Course, Data Analyst, CALCULATE Function, Power BI Dashboard, Time Intelligence, Microsoft Power BI, DAX Functions, BI Developer]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306193Fri, 15 May 2026 14:59:27 +0000fertMaster DAX from beginner to advanced with this complete Power BI DAX course 🚀 In this full-length tutorial, you’ll learn how real business calculations work inside Power BI using measures, CALCULATE, filter context, time intelligence, KPIs, and...In this full-length tutorial, you’ll learn how real business calculations work inside Power BI using measures, CALCULATE, filter context, time intelligence, KPIs, and advanced DAX concepts used by data analysts in production dashboards.

Whether you're preparing for data analyst roles, improving Power BI skills, or building real dashboards — this video will give you a strong DAX foundation.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

Dataset link - https://drive.google.com/drive/folders/1qKLoBe-Na5ZAbmiNleqSBmYh33UCKybX?usp=sharing

📘 Notes Link:
https://www.notion.so/PowerBI-DAX-Playbook-35d0ec11c39c8074b29ad023a8f0f4b8?source=copy_link

⏱️ Timestamps-
00:00:00 - 00:07:22 — Intro
00:07:22 - 00:43:27 — Module Overview
Module 1
00:43:27 - 01:30:32 — Aggregation Functions
01:33:32 - 01:50:52 — Logical Functions
01:56:52 - 02:25:47 — Text Functions
02:26:47 - 02:57:19 — Project Implementation
03:02:19 - 03:04:08 — Outro
Module 2
03:04:00 - 03:05:39 — Introduction
03:05:39 - 03:20:43 — Filter Context Deep Dive
03:20:51 - 03:55:54 — CALCULATE Function Explained
03:58:55 - 04:35:17 — Filter Functions Deep Dive
05:33:17 - 05:09:59 — Iterative Functions & Best Practices
05:09:59 - 05:35:30 — Real-World Project Implementation
05:35:30 - 05:37:18 — Outro & Summary
Module 3
05:37:00 - 05:43:39 — Introduction
05:43:39 - 06:27:43 — Time Intelligence Functions
06:27:51 - 06:58:54 — Comparison & Growth Time Calculations
06:58:55 - 07:22:17 — Project Using Time Intelligence Functions
07:22:17 - 07:23:59 — Outro & Summary
Module 4
07:24:00 - 07:45:39 — Introduction to Data Modeling
07:45:39 - 08:45:43 — Practical Implementation & Project
08:45:43 - 08:46:30 — Outro & Summary
Module 5
08:46:40 - 08:50:32 — Introduction to Advanced DAX
08:50:32 - 09:11:52 — Rank Functions
09:11:52 - 09:26:47 — Table Functions
09:26:47 - 09:44:19 — More DAX Functions
09:44:19 - 09:45:05 — Practice Project & Summary

🌐 Connect With Sheryians
🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/AEPZJT3Zer

Power BI, DAX, Power BI Tutorial, Data Analytics, Business Intelligence, DAX Tutorial, Power BI Full Course, Data Analyst, CALCULATE Function, Power BI Dashboard, Time Intelligence, Microsoft Power BI, DAX Functions, BI Developer]]>35158falsefullhttps://www.spreaker.com/episode/ai-vs-ml-vs-dl-vs-data-science-vs-genai-explained-simply--74883298#ai #MachineLearning #DataScience #GenAI
#DeepLearning #ArtificialIntelligence

Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

In this video, I break down the most confusing
terms in tech — AI, ML, DL, Data Analytics,
Data Science and Generative AI — with simple
examples and a clear roadmap for beginners.

🔹 What is AI?
🔹 How is ML different from AI?
🔹 What is Deep Learning?
🔹 Where does Data Science fit?
🔹 What is Generative AI?
🔹 Complete Learning Roadmap

Perfect for students who are just starting out
and want clarity before picking a career path.

🎓 Instructor in this video - Akarsh Vyas

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306227Wed, 13 May 2026 14:00:42 +0000fertWelcome to Sheryians AI School #ai #MachineLearning #DataScience #GenAI #DeepLearning #ArtificialIntelligence Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart...#ai #MachineLearning #DataScience #GenAI
#DeepLearning #ArtificialIntelligence

Your one-stop destination to explore Artificial Intelligence, Machine Learning, Data Science, Data Analysis, Python, and everything smart enough to shape the future.

In this video, I break down the most confusing
terms in tech — AI, ML, DL, Data Analytics,
Data Science and Generative AI — with simple
examples and a clear roadmap for beginners.

🔹 What is AI?
🔹 How is ML different from AI?
🔹 What is Deep Learning?
🔹 Where does Data Science fit?
🔹 What is Generative AI?
🔹 Complete Learning Roadmap

Perfect for students who are just starting out
and want clarity before picking a career path.

🎓 Instructor in this video - Akarsh Vyas

🌐 Connect With Sheryians - https://sheryians.com/

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>1406falsefullhttps://www.spreaker.com/episode/ai-video-assistant-with-rag-full-project-in-python--74883290from scratch using Python — completely FREE!

No more paying ₹2000/month for Otter.ai or Fireflies.
This tool does everything they do and more.

✅ WHAT THIS TOOL DOES:
→ Takes any YouTube URL or audio/video file as input
→ Transcribes English meetings using local Whisper AI
→ Transcribes Hindi & Hinglish meetings using Sarvam AI
→ Summarises the full meeting in bullet points
→ Extracts action items with owner and deadline
→ Extracts key decisions made in the meeting
→ Extracts open questions and follow-ups
→ Lets you CHAT with your meeting using RAG + ChromaDB
→ Export full report as PDF or TXT

🛠️ TECH STACK:
→ Python
→ OpenAI Whisper (local, free)
→ Sarvam AI (Hindi/Hinglish transcription)
→ LangChain LCEL (modern pipeline)
→ Mistral AI (free API)
→ ChromaDB (vector database for RAG)
→ HuggingFace Embeddings (local, free)
→ Streamlit (UI)

📂 SOURCE CODE:
GitHub Link → https://github.com/AkarshVyas/AI-Video-Assistant-

🔑 GET YOUR FREE API KEYS:
Mistral AI → https://console.mistral.ai
Sarvam AI → https://dashboard.sarvam.ai

📦 INSTALL DEPENDENCIES:
pip install -r requirements.txt

Timestamps -
00:00:00 - 00:02:43 Introduction & Project Overview
00:02:43 - 00:06:30 Intro
00:06:30 - 00:08:00 About the AI Video Assistant Project
00:08:00 - 00:11:00 Tools Used & API Connections Setup
00:11:00 - 00:12:35 Project Folder Structure & Virtual Environment Setup
00:12:35 - 00:16:17 .env File Configuration & Mistral AI API Setup
00:16:17 - 00:19:29 requirements.txt File Creation & Dependencies
00:19:29 - 00:22:10 utils/audio_processor.py
00:22:10 - 00:27:40 Import Required Libraries
00:27:40 - 00:36:15 Extract Audio from Video
00:36:15 - 00:49:30 Audio Processing & Optimization
00:49:30 - 00:55:20 transcriber.py
00:55:20 - 01:07:00 Generate Transcript using Speech-to-Text
01:07:00 - 01:15:32 Testing File Creation & Execution
01:15:32 - 01:20:45 translator.py
01:20:45 - 01:28:10 Translate Hindi/English Transcript to Clean English
01:28:10 - 01:33:00 Mistral AI + LangChain Integration
01:33:00 - 01:40:22 summarise.py
01:40:22 - 01:54:00 Structured Transcript Summarization using LangChain + Mistral
01:54:00 - 02:01:18 extractor.py
02:01:18 - 02:14:12 Extract Action Items, Decisions & Questions
02:14:12 - 02:20:40 vector_store.py
02:20:40 - 02:30:00 Create Embeddings & Store Vectors
02:30:00 - 02:37:35 rag_engine.py
02:37:35 - 02:47:28 Retrieval-Augmented Generation (RAG) Workflow
02:47:28 - 02:50:12 main.py
02:50:12 - 02:57:00 Generate AI Title, Summary, Questions & Key Decisions
02:57:00 - 03:03:14 Chat with AI Model using RAG
03:03:14 - END Final Streamlit UI Creation & Demo

🌐 Connect With Sheryians - https://sheryians.com/
Paid program -https://sheryians.com/courses/68da779296b89547293c7a26
📷 Instagram -https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

#Python #AI #LangChain #MachineLearning #OpenAI
#Whisper #RAG #ChromaDB #MistralAI #SarvamAI
#AIProject #PythonProject #LLM #GenerativeAI
#ArtificialIntelligence #MLProject #AITools]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306216Fri, 08 May 2026 14:01:43 +0000fert🎙️ In this video, I built a complete AI Meeting Assistant from scratch using Python — completely FREE! No more paying ₹2000/month for Otter.ai or Fireflies. This tool does everything they do and more. ✅ WHAT THIS TOOL DOES: → Takes any YouTube URL...from scratch using Python — completely FREE!

No more paying ₹2000/month for Otter.ai or Fireflies.
This tool does everything they do and more.

✅ WHAT THIS TOOL DOES:
→ Takes any YouTube URL or audio/video file as input
→ Transcribes English meetings using local Whisper AI
→ Transcribes Hindi & Hinglish meetings using Sarvam AI
→ Summarises the full meeting in bullet points
→ Extracts action items with owner and deadline
→ Extracts key decisions made in the meeting
→ Extracts open questions and follow-ups
→ Lets you CHAT with your meeting using RAG + ChromaDB
→ Export full report as PDF or TXT

🛠️ TECH STACK:
→ Python
→ OpenAI Whisper (local, free)
→ Sarvam AI (Hindi/Hinglish transcription)
→ LangChain LCEL (modern pipeline)
→ Mistral AI (free API)
→ ChromaDB (vector database for RAG)
→ HuggingFace Embeddings (local, free)
→ Streamlit (UI)

📂 SOURCE CODE:
GitHub Link → https://github.com/AkarshVyas/AI-Video-Assistant-

🔑 GET YOUR FREE API KEYS:
Mistral AI → https://console.mistral.ai
Sarvam AI → https://dashboard.sarvam.ai

📦 INSTALL DEPENDENCIES:
pip install -r requirements.txt

Timestamps -
00:00:00 - 00:02:43 Introduction & Project Overview
00:02:43 - 00:06:30 Intro
00:06:30 - 00:08:00 About the AI Video Assistant Project
00:08:00 - 00:11:00 Tools Used & API Connections Setup
00:11:00 - 00:12:35 Project Folder Structure & Virtual Environment Setup
00:12:35 - 00:16:17 .env File Configuration & Mistral AI API Setup
00:16:17 - 00:19:29 requirements.txt File Creation & Dependencies
00:19:29 - 00:22:10 utils/audio_processor.py
00:22:10 - 00:27:40 Import Required Libraries
00:27:40 - 00:36:15 Extract Audio from Video
00:36:15 - 00:49:30 Audio Processing & Optimization
00:49:30 - 00:55:20 transcriber.py
00:55:20 - 01:07:00 Generate Transcript using Speech-to-Text
01:07:00 - 01:15:32 Testing File Creation & Execution
01:15:32 - 01:20:45 translator.py
01:20:45 - 01:28:10 Translate Hindi/English Transcript to Clean English
01:28:10 - 01:33:00 Mistral AI + LangChain Integration
01:33:00 - 01:40:22 summarise.py
01:40:22 - 01:54:00 Structured Transcript Summarization using LangChain + Mistral
01:54:00 - 02:01:18 extractor.py
02:01:18 - 02:14:12 Extract Action Items, Decisions & Questions
02:14:12 - 02:20:40 vector_store.py
02:20:40 - 02:30:00 Create Embeddings & Store Vectors
02:30:00 - 02:37:35 rag_engine.py
02:37:35 - 02:47:28 Retrieval-Augmented Generation (RAG) Workflow
02:47:28 - 02:50:12 main.py
02:50:12 - 02:57:00 Generate AI Title, Summary, Questions & Key Decisions
02:57:00 - 03:03:14 Chat with AI Model using RAG
03:03:14 - END Final Streamlit UI Creation & Demo

🌐 Connect With Sheryians - https://sheryians.com/
Paid program -https://sheryians.com/courses/68da779296b89547293c7a26
📷 Instagram -https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

#Python #AI #LangChain #MachineLearning #OpenAI
#Whisper #RAG #ChromaDB #MistralAI #SarvamAI
#AIProject #PythonProject #LLM #GenerativeAI
#ArtificialIntelligence #MLProject #AITools]]>11515falsefullhttps://www.spreaker.com/episode/traditional-rag-vs-vectorless-rag-page-indexing-what-should-you-use--74883271Everyone is talking about Vectorless RAG and PageIndex like it is going to replace traditional RAG forever. In this video I break down exactly how both work, when to use which, and give you the honest verdict nobody else is giving.
We cover:

How traditional RAG actually works
The real problems with vector based retrieval
How PageIndex builds a tree without embeddings
When Vectorless RAG wins and when it completely fails
Final verdict — which one should YOU use

Vectorless RAG is powerful but it is not for everyone. Watch till the end before you make the switch.


🎓 Speaker in this video
Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/
Paid program - https://sheryians.com/courses/68da779296b89547293c7a26

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306196Wed, 29 Apr 2026 14:05:29 +0000fertWelcome to Sheryians AI School Everyone is talking about Vectorless RAG and PageIndex like it is going to replace traditional RAG forever. In this video I break down exactly how both work, when to use which, and give you the honest verdict nobody else...Everyone is talking about Vectorless RAG and PageIndex like it is going to replace traditional RAG forever. In this video I break down exactly how both work, when to use which, and give you the honest verdict nobody else is giving.
We cover:

How traditional RAG actually works
The real problems with vector based retrieval
How PageIndex builds a tree without embeddings
When Vectorless RAG wins and when it completely fails
Final verdict — which one should YOU use

Vectorless RAG is powerful but it is not for everyone. Watch till the end before you make the switch.


🎓 Speaker in this video
Akarsh Vyas

❤️ Support the Channel
Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

🌐 Connect With Sheryians - https://sheryians.com/
Paid program - https://sheryians.com/courses/68da779296b89547293c7a26

📷 Instagram - https://www.instagram.com/sheryians.ai?igsh=empvcXdkanlrN3Iz
🎮 Discord - https://discord.gg/HFH2V54WZ

SheryiansAISchool, ArtificialIntelligence, MachineLearning, DataScience, DataAnalysis, Python, AIForBeginners, MLForBeginners, DataScienceCareer, AICourse]]>1837falsefullhttps://www.spreaker.com/episode/the-truth-about-ai-and-jobs-nobody-is-telling-you-2025-data--74883304Dario Amodei, CEO of Anthropic, says AI could replace 50% of entry-level white-collar jobs in the next 5 years.
Mustafa Suleyman, CEO of Microsoft AI, says most professional work could be automated within the next 12–18 months.
And the scary part? It’s already happening.

Speaker - Akarsh Vyas

In this video, we break down:

✅ Complete history of job market shifts — from Engineering Boom → IT Boom → Startup Era → AI Revolution
✅ How COVID permanently changed the IT industry and hiring patterns
✅ Which companies are already replacing employees with AI (real-world examples)
✅ What the World Economic Forum (WEF) Future of Jobs Report 2025 actually says
✅ Why AI-skilled professionals are already earning significantly higher salaries
✅ What students, freshers, and working professionals should do RIGHT NOW to stay relevant

If you are a student, fresher, developer, engineer, or someone confused about your career path — this video might completely change how you think about your future.

🔗Timestamps -
00:00:00 - 00:02:24 - The Problem
00:02:24 - 00:05:04 - The History of Job Trends
00:05:04 - 00:07:50 - The Shift after Covid
00:07:50 - 00:10:58 - The Rise of AI
00:10:58 - 00:14:45 - Job Market reality
00:14:45 - 00:16:56 - What should students do now
00:16:56 - 00:18:44 - Future of Jobs

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians

👍 Like the video
💬 Comment your thoughts:
“Will AI replace jobs or just weak engineers?”
🔔 Subscribe for more practical

ai jobs, ai replacing jobs, will ai replace jobs, future of jobs 2025, ai and jobs, artificial intelligence jobs, job market 2025, ai career advice, future of work, layoffs due to ai, freshers jobs 2025, engineering jobs future, software engineer future, ai vs developers, chatgpt jobs, gen ai jobs, students career advice, ai automation jobs, white collar jobs ai]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306212Sat, 25 Apr 2026 14:00:32 +0000fertThe job market is changing faster than ever — and most people are still not prepared. Dario Amodei, CEO of Anthropic, says AI could replace 50% of entry-level white-collar jobs in the next 5 years. Mustafa Suleyman, CEO of Microsoft AI, says most...Dario Amodei, CEO of Anthropic, says AI could replace 50% of entry-level white-collar jobs in the next 5 years.
Mustafa Suleyman, CEO of Microsoft AI, says most professional work could be automated within the next 12–18 months.
And the scary part? It’s already happening.

Speaker - Akarsh Vyas

In this video, we break down:

✅ Complete history of job market shifts — from Engineering Boom → IT Boom → Startup Era → AI Revolution
✅ How COVID permanently changed the IT industry and hiring patterns
✅ Which companies are already replacing employees with AI (real-world examples)
✅ What the World Economic Forum (WEF) Future of Jobs Report 2025 actually says
✅ Why AI-skilled professionals are already earning significantly higher salaries
✅ What students, freshers, and working professionals should do RIGHT NOW to stay relevant

If you are a student, fresher, developer, engineer, or someone confused about your career path — this video might completely change how you think about your future.

🔗Timestamps -
00:00:00 - 00:02:24 - The Problem
00:02:24 - 00:05:04 - The History of Job Trends
00:05:04 - 00:07:50 - The Shift after Covid
00:07:50 - 00:10:58 - The Rise of AI
00:10:58 - 00:14:45 - Job Market reality
00:14:45 - 00:16:56 - What should students do now
00:16:56 - 00:18:44 - Future of Jobs

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians

👍 Like the video
💬 Comment your thoughts:
“Will AI replace jobs or just weak engineers?”
🔔 Subscribe for more practical

ai jobs, ai replacing jobs, will ai replace jobs, future of jobs 2025, ai and jobs, artificial intelligence jobs, job market 2025, ai career advice, future of work, layoffs due to ai, freshers jobs 2025, engineering jobs future, software engineer future, ai vs developers, chatgpt jobs, gen ai jobs, students career advice, ai automation jobs, white collar jobs ai]]>1125falsefullhttps://www.spreaker.com/episode/build-a-multi-agent-ai-research-system-with-langchain-full-project--74883318AI and learn how to orchestrate multiple specialized AI agents that work together as a pipeline searching the web, scraping content, writing reports, and reviewing them automatically.

Whether you are an intermediate AI developer or someone looking to move from basic LangChain usage to real agentic systems, this project will show you exactly how production-style multi-agent workflows are designed and built.

👨‍🏫 Instructor – Akarsh Vyas walking you through every line of code, every design decision, and every agent interaction in a clear and practical way.

📂Code Files - https://github.com/AkarshVyas/Multi-agent-research-system

What You Will Learn in This Video
* What are AI Agents and how they differ from simple LLM chains
* How to build a multi-agent pipeline with LangChain
* Designing a Search Agent that retrieves live, reliable web data
* Designing a Reader Agent that scrapes and extracts deep content from URLs
* Using Writer Chains to generate structured, detailed research reports
* Using Critic Chains to automatically review and score AI-generated output
* How agents pass state to each other through a shared pipeline
* Building a professional Streamlit UI for your multi-agent system
* How to structure real-world agentic AI projects cleanly

Timestamps -
00:00:00 - 00:01:31 Introduction
00:01:31 - 00:08:47 Understanding the Pipeline
00:08:47 - 00:17:51 Project Setup & Configuration
00:17:51 - 00:45:14 Building Custom Tools
00:45:14 - 01:16:02 AI Agents & LCEL Logic
01:16:02 - 01:48:19 Final Pipeline & Live Results
01:48:19 - 02:00:14 Generating the UI
02:00:14 - 02:01:04 Outro & Summary


🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/
🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians

Don't forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

multi agent ai system , langchain agents tutorial , agentic ai project , ai research agent , langchain multi agent , streamlit ai app , llm agents 2026 , langchain tools and agents , ai pipeline project , generative ai project 2026 , langchain full project , ai agents for beginners , research automation ai , langchain agent tutorial , agentic workflow langchain]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306181Mon, 13 Apr 2026 14:45:01 +0000fertIn this hands-on project tutorial, you will build a complete Multi-Agent AI Research System from scratch using LangChain and Large Language Models. This is a practical, project-first session where you go beyond single-prompt AI and learn how to...AI and learn how to orchestrate multiple specialized AI agents that work together as a pipeline searching the web, scraping content, writing reports, and reviewing them automatically.

Whether you are an intermediate AI developer or someone looking to move from basic LangChain usage to real agentic systems, this project will show you exactly how production-style multi-agent workflows are designed and built.

👨‍🏫 Instructor – Akarsh Vyas walking you through every line of code, every design decision, and every agent interaction in a clear and practical way.

📂Code Files - https://github.com/AkarshVyas/Multi-agent-research-system

What You Will Learn in This Video
* What are AI Agents and how they differ from simple LLM chains
* How to build a multi-agent pipeline with LangChain
* Designing a Search Agent that retrieves live, reliable web data
* Designing a Reader Agent that scrapes and extracts deep content from URLs
* Using Writer Chains to generate structured, detailed research reports
* Using Critic Chains to automatically review and score AI-generated output
* How agents pass state to each other through a shared pipeline
* Building a professional Streamlit UI for your multi-agent system
* How to structure real-world agentic AI projects cleanly

Timestamps -
00:00:00 - 00:01:31 Introduction
00:01:31 - 00:08:47 Understanding the Pipeline
00:08:47 - 00:17:51 Project Setup & Configuration
00:17:51 - 00:45:14 Building Custom Tools
00:45:14 - 01:16:02 AI Agents & LCEL Logic
01:16:02 - 01:48:19 Final Pipeline & Live Results
01:48:19 - 02:00:14 Generating the UI
02:00:14 - 02:01:04 Outro & Summary


🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/
🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians

Don't forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.

multi agent ai system , langchain agents tutorial , agentic ai project , ai research agent , langchain multi agent , streamlit ai app , llm agents 2026 , langchain tools and agents , ai pipeline project , generative ai project 2026 , langchain full project , ai agents for beginners , research automation ai , langchain agent tutorial , agentic workflow langchain]]>7265falsefullhttps://www.spreaker.com/episode/generative-ai-full-course-part-3-tools-ai-agents-tool-calling-apis-langchain--74883299
This is the next step in our Generative AI series, where we move beyond fundamentals like runnables and tools and actually build a system that can think, make decisions, and take actions intelligently.
Instead of just learning concepts, you’ll implement a working AI agent step by step — just like real-world AI systems.

Whether you are a beginner or a developer, this video will give you clarity on how modern AI systems interact with tools, fetch real-world data, and solve complex problems.

👨‍🏫 Instructor – Akarsh Vyas

📄 Notes (Part 1 & 2)
https://drive.google.com/file/d/1yfySeYDONghk46oKaf1FmcGqzCt_yDCj/view?usp=sharing

💻 Code
https://github.com/AkarshVyas/Generative-AI-video3-

📚 What You Will Learn
• What AI Agents are and how they actually work
• Difference between tools and agents
• Understanding the agent loop (LLM → Tool → Result → LLM)
• How to build a manual agent from scratch
• How LLM decides which tool to use
• Integrating real-world APIs (weather, news)
• Adding human-in-the-loop for control and safety
• Understanding create_agent and abstraction in LangChain
• Debugging and controlling agent behavior

⚡ Project You Will Build

A complete AI Agent system that:
• Takes user queries
• Decides whether to call a tool
• Fetches real-time data (weather, news)
• Processes tool outputs
• Generates an intelligent final response

🛠 Tech Stack Used
• Python
• LangChain
• OpenAI / Mistral LLM
• Tavily API (Search / News)
• OpenWeather API

🌐 Connect With Sheryians

🌐 Website – https://sheryians.com/
🔗 Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians

Don’t forget to LIKE 👍, SUBSCRIBE 🔔 and COMMENT 💬 if you want more real-world Generative AI projects.

ai agents tutorial , langchain agents project , tool calling llm , ai agent python project , generative ai agents , build ai assistant , langchain tools and agents , openai agent tutorial , gen ai project , ai system design , agentic ai tutorial , llm tools integration , sheryians ai school]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306211Wed, 01 Apr 2026 14:30:13 +0000fertIn this project-based Generative AI tutorial, you will build a complete AI Agent system from scratch using real-world tools and APIs. This is the next step in our Generative AI series, where we move beyond fundamentals like runnables and tools and...
This is the next step in our Generative AI series, where we move beyond fundamentals like runnables and tools and actually build a system that can think, make decisions, and take actions intelligently.
Instead of just learning concepts, you’ll implement a working AI agent step by step — just like real-world AI systems.

Whether you are a beginner or a developer, this video will give you clarity on how modern AI systems interact with tools, fetch real-world data, and solve complex problems.

👨‍🏫 Instructor – Akarsh Vyas

📄 Notes (Part 1 & 2)
https://drive.google.com/file/d/1yfySeYDONghk46oKaf1FmcGqzCt_yDCj/view?usp=sharing

💻 Code
https://github.com/AkarshVyas/Generative-AI-video3-

📚 What You Will Learn
• What AI Agents are and how they actually work
• Difference between tools and agents
• Understanding the agent loop (LLM → Tool → Result → LLM)
• How to build a manual agent from scratch
• How LLM decides which tool to use
• Integrating real-world APIs (weather, news)
• Adding human-in-the-loop for control and safety
• Understanding create_agent and abstraction in LangChain
• Debugging and controlling agent behavior

⚡ Project You Will Build

A complete AI Agent system that:
• Takes user queries
• Decides whether to call a tool
• Fetches real-time data (weather, news)
• Processes tool outputs
• Generates an intelligent final response

🛠 Tech Stack Used
• Python
• LangChain
• OpenAI / Mistral LLM
• Tavily API (Search / News)
• OpenWeather API

🌐 Connect With Sheryians

🌐 Website – https://sheryians.com/
🔗 Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians

Don’t forget to LIKE 👍, SUBSCRIBE 🔔 and COMMENT 💬 if you want more real-world Generative AI projects.

ai agents tutorial , langchain agents project , tool calling llm , ai agent python project , generative ai agents , build ai assistant , langchain tools and agents , openai agent tutorial , gen ai project , ai system design , agentic ai tutorial , llm tools integration , sheryians ai school]]>14770falsefullhttps://www.spreaker.com/episode/what-the-industry-actually-wants-in-2026-what-really-matters--74883309There is a lot of confusion online. Some people say AI will replace all jobs, while others claim it’s the best career path. In this session, we focus on actual industry reality, based on hiring trends, skill requirements, and real-world expectations.

We cover the global job market, India hiring landscape, freshers placement reality, and what companies actually expect from candidates in 2026.
If you are a college student or someone planning to start a career in AI, ML, or Data Science, this video will give you a clear direction on what really matters and how to approach the next 6–12 months.

👨‍🏫 Speaker – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

📚 What You Will Learn in This Video
• Current reality of AI, ML & Data Science careers in 2026
• Global job market trends and role evolution
• India hiring landscape and opportunities
• Freshers hiring reality (on-campus vs off-campus)
• Key skills companies expect in 2026
• Importance of projects, portfolio, and real implementations
• AI tools, ML concepts, and data fundamentals required
• Common myths vs actual industry reality
• 6–12 month roadmap to start your career
• How to stand out as a fresher in a competitive market

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI, Data Science, and Tech content, and COMMENT 💬 your thoughts below!

ai careers 2026, ai jobs india, data science careers 2026, machine learning careers 2026, ai job market 2026, ai vs data science career, ai jobs for freshers, data science jobs for freshers, ai future scope, data science roadmap, machine learning roadmap, tech careers india]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306186Sat, 28 Mar 2026 14:59:08 +0000fertIn this video, we break down the real truth about AI, Machine Learning, and Data Science careers in 2026 — without hype or fear. There is a lot of confusion online. Some people say AI will replace all jobs, while others claim it’s the best career...There is a lot of confusion online. Some people say AI will replace all jobs, while others claim it’s the best career path. In this session, we focus on actual industry reality, based on hiring trends, skill requirements, and real-world expectations.

We cover the global job market, India hiring landscape, freshers placement reality, and what companies actually expect from candidates in 2026.
If you are a college student or someone planning to start a career in AI, ML, or Data Science, this video will give you a clear direction on what really matters and how to approach the next 6–12 months.

👨‍🏫 Speaker – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

📚 What You Will Learn in This Video
• Current reality of AI, ML & Data Science careers in 2026
• Global job market trends and role evolution
• India hiring landscape and opportunities
• Freshers hiring reality (on-campus vs off-campus)
• Key skills companies expect in 2026
• Importance of projects, portfolio, and real implementations
• AI tools, ML concepts, and data fundamentals required
• Common myths vs actual industry reality
• 6–12 month roadmap to start your career
• How to stand out as a fresher in a competitive market

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI, Data Science, and Tech content, and COMMENT 💬 your thoughts below!

ai careers 2026, ai jobs india, data science careers 2026, machine learning careers 2026, ai job market 2026, ai vs data science career, ai jobs for freshers, data science jobs for freshers, ai future scope, data science roadmap, machine learning roadmap, tech careers india]]>376falsefullhttps://www.spreaker.com/episode/build-an-end-to-end-business-analytics-dashboard-in-power-bi-food-delivery-app-data--74883306
This session focuses on creating a full end-to-end data analytics workflow — starting from raw dataset exploration, data cleaning in Power Query, data modeling, and finally building an interactive business dashboard to generate actionable insights.

We will be working on a Zomato style food delivery dataset, where you’ll understand how real-world business metrics like orders, revenue, customers, and performance trends are analyzed using Power BI.

Whether you are a beginner in Data Analytics, learning Power BI, or building your portfolio, this project will give you a complete understanding of how professional dashboards are built in the industry.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

💻 Project Files
https://drive.google.com/drive/folders/1YDEvCG-Q3zRzDWjMeVc5vAJywfQMU3SL?usp=drive_link

📚 What You Will Learn in This Video
• Understanding real-world food delivery dataset structure
• Importing and inspecting data in Power BI
• Data cleaning and transformation using Power Query
• Creating structured tables (Orders, Customers, Restaurants, Date)
• Building relationships and data modeling
• Creating calculated columns and DAX measures
• Building key business metrics (Revenue, Orders, Customers, AOV)
• Designing multiple dashboard pages with insights
• Adding slicers, filters, and interactions
• Creating an industry-level Business Analytics Dashboard

⏱️ Timestamps
00:00:00 - 00:01:09 Introduction
00:01:09 - 00:19:22 ETL Process & Data Modeling
00:19:22 - 00:49:38 Calculated Columns & Measures (DAX)
00:49:38 - 01:20:37 Executive Overview Dashboard
01:20:37 - 01:39:51 Customer Analytics Report
01:39:51 - 02:00:51 Restaurant Performance Analysis
02:00:51 - 02:52:57 Delivery Insights, Advanced Features & Drillthrough
02:52:57 - 02:54:50 Outro

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more Data Analytics, Power BI, and AI content, and COMMENT 💬 your thoughts or questions below!

power bi project , data analytics project , power bi dashboard , business analytics dashboard , zomato data analysis , swiggy data analysis , power bi tutorial , data analyst project , dashboard project power bi , end to end power bi project , data analytics tutorial , business intelligence project , power bi portfolio project , dax tutorial , power query tutorial , sheryians ai school]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306195Tue, 24 Mar 2026 14:01:29 +0000fertIn this complete Industry-Level Business Analytics Project, you will learn how to build a real-world analytics dashboard using Power BI. This session focuses on creating a full end-to-end data analytics workflow — starting from raw dataset...
This session focuses on creating a full end-to-end data analytics workflow — starting from raw dataset exploration, data cleaning in Power Query, data modeling, and finally building an interactive business dashboard to generate actionable insights.

We will be working on a Zomato style food delivery dataset, where you’ll understand how real-world business metrics like orders, revenue, customers, and performance trends are analyzed using Power BI.

Whether you are a beginner in Data Analytics, learning Power BI, or building your portfolio, this project will give you a complete understanding of how professional dashboards are built in the industry.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

💻 Project Files
https://drive.google.com/drive/folders/1YDEvCG-Q3zRzDWjMeVc5vAJywfQMU3SL?usp=drive_link

📚 What You Will Learn in This Video
• Understanding real-world food delivery dataset structure
• Importing and inspecting data in Power BI
• Data cleaning and transformation using Power Query
• Creating structured tables (Orders, Customers, Restaurants, Date)
• Building relationships and data modeling
• Creating calculated columns and DAX measures
• Building key business metrics (Revenue, Orders, Customers, AOV)
• Designing multiple dashboard pages with insights
• Adding slicers, filters, and interactions
• Creating an industry-level Business Analytics Dashboard

⏱️ Timestamps
00:00:00 - 00:01:09 Introduction
00:01:09 - 00:19:22 ETL Process & Data Modeling
00:19:22 - 00:49:38 Calculated Columns & Measures (DAX)
00:49:38 - 01:20:37 Executive Overview Dashboard
01:20:37 - 01:39:51 Customer Analytics Report
01:39:51 - 02:00:51 Restaurant Performance Analysis
02:00:51 - 02:52:57 Delivery Insights, Advanced Features & Drillthrough
02:52:57 - 02:54:50 Outro

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more Data Analytics, Power BI, and AI content, and COMMENT 💬 your thoughts or questions below!

power bi project , data analytics project , power bi dashboard , business analytics dashboard , zomato data analysis , swiggy data analysis , power bi tutorial , data analyst project , dashboard project power bi , end to end power bi project , data analytics tutorial , business intelligence project , power bi portfolio project , dax tutorial , power query tutorial , sheryians ai school]]>10485falsefullhttps://www.spreaker.com/episode/generative-ai-full-course-part-2-document-loaders-text-splitters-vector-db-rag-langchain--74883297
This is Part 2 of our Generative AI series, where we move beyond fundamentals and implement a production-style AI system that can read documents and answer questions intelligently. Instead of just theory, you’ll build a working AI application step by step.

Whether you are a beginner or a developer, this video will help you understand how modern AI systems like ChatGPT work with private data using RAG architecture.

👨‍🏫 Instructor – Akarsh Vyas guiding you step-by-step through building a real-world RAG system in a simple and practical way.

📚 What You Will Learn in This Video
• What Document Loaders are and how they load PDFs into LangChain
• How Text Splitters break large documents into manageable chunks
• Understanding Embeddings and semantic meaning of text
• How Vector Databases store and retrieve information
• What Retrievers are and how they fetch relevant context
• How all components connect to form a complete RAG pipeline
• How AI systems answer questions using external knowledge

📝 Notes -
https://drive.google.com/file/d/1pRtg6YWuLPFamb6GcW4Y3s7hOdOI9FR8/view?usp=sharing

💻 Code -
https://github.com/AkarshVyas/GenAI-part2-Rag-implementation

⚡ Project You Will Build
A complete AI system that:

• Loads a PDF book
• Splits it into smaller chunks
• Converts text into embeddings
• Stores them inside a vector database
• Uses a retriever to fetch relevant data
• Sends context to an LLM for answering queries

⏱️ Timestamps -
00:00:00 - 00:01:48 - Introduction
00:01:48 - 00:17:54 - Learning & Development Plan
00:17:54 - 00:30:10 - Basic Setup
00:30:10 - 00:58:45 - Document Loaders
00:58:45 - 01:42:29 - Text Splitter
01:42:29 - 02:31:37 - Vector Stores
02:31:37 - 03:11:24 - Retrievers
03:11:24 - 03:41:24 - Completing the Project

🛠 Tech Stack Used
• Python
• LangChain
• Chroma (Vector Database)
• OpenAI Embeddings
• Mistral LLM

🌐 Connect With Sheryians -

🌐 Website - https://sheryians.com/
🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more Generative AI projects, and COMMENT 💬 if you want more real-world AI tutorials.

generative ai rag tutorial , rag langchain project , retrieval augmented generation tutorial , langchain rag , ai project tutorial , build rag system , vector database tutorial , embeddings explained , ai with pdf chatbot , llm rag project , gen ai projects , python ai project , rag explained , langchain full course , ai development tutorial]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306185Tue, 17 Mar 2026 14:01:37 +0000fertIn this project-based Generative AI tutorial, you will build a complete Retrieval-Augmented Generation (RAG) system from scratch using real-world concepts and tools. This is Part 2 of our Generative AI series, where we move beyond fundamentals and...
This is Part 2 of our Generative AI series, where we move beyond fundamentals and implement a production-style AI system that can read documents and answer questions intelligently. Instead of just theory, you’ll build a working AI application step by step.

Whether you are a beginner or a developer, this video will help you understand how modern AI systems like ChatGPT work with private data using RAG architecture.

👨‍🏫 Instructor – Akarsh Vyas guiding you step-by-step through building a real-world RAG system in a simple and practical way.

📚 What You Will Learn in This Video
• What Document Loaders are and how they load PDFs into LangChain
• How Text Splitters break large documents into manageable chunks
• Understanding Embeddings and semantic meaning of text
• How Vector Databases store and retrieve information
• What Retrievers are and how they fetch relevant context
• How all components connect to form a complete RAG pipeline
• How AI systems answer questions using external knowledge

📝 Notes -
https://drive.google.com/file/d/1pRtg6YWuLPFamb6GcW4Y3s7hOdOI9FR8/view?usp=sharing

💻 Code -
https://github.com/AkarshVyas/GenAI-part2-Rag-implementation

⚡ Project You Will Build
A complete AI system that:

• Loads a PDF book
• Splits it into smaller chunks
• Converts text into embeddings
• Stores them inside a vector database
• Uses a retriever to fetch relevant data
• Sends context to an LLM for answering queries

⏱️ Timestamps -
00:00:00 - 00:01:48 - Introduction
00:01:48 - 00:17:54 - Learning & Development Plan
00:17:54 - 00:30:10 - Basic Setup
00:30:10 - 00:58:45 - Document Loaders
00:58:45 - 01:42:29 - Text Splitter
01:42:29 - 02:31:37 - Vector Stores
02:31:37 - 03:11:24 - Retrievers
03:11:24 - 03:41:24 - Completing the Project

🛠 Tech Stack Used
• Python
• LangChain
• Chroma (Vector Database)
• OpenAI Embeddings
• Mistral LLM

🌐 Connect With Sheryians -

🌐 Website - https://sheryians.com/
🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more Generative AI projects, and COMMENT 💬 if you want more real-world AI tutorials.

generative ai rag tutorial , rag langchain project , retrieval augmented generation tutorial , langchain rag , ai project tutorial , build rag system , vector database tutorial , embeddings explained , ai with pdf chatbot , llm rag project , gen ai projects , python ai project , rag explained , langchain full course , ai development tutorial]]>13299falsefullhttps://www.spreaker.com/episode/build-an-industry-level-data-analytics-dashboard-project-postgresql-power-bi--74883328
This session focuses on building a full end-to-end data analytics project, starting from raw dataset ingestion in PostgreSQL to creating optimized analytical views and finally connecting the database with Power BI to perform business analysis and build powerful data insights.

Whether you are a Data Analytics beginner, SQL learner, or someone preparing portfolio projects, this session will help you understand how real analytics systems are structured and how data analysts work with databases and BI tools in the industry.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

💻 Project Files
https://drive.google.com/drive/folders/1XEyJDvVJdy8WaOBQjempuzpuW7dV-Pxw?usp=drive_link

📚 What You Will Learn in This Video

• Understanding the structure of a real-world e-commerce dataset
• Setting up PostgreSQL database for analytics workflows
• Creating tables and importing large CSV datasets
• Data validation, cleaning and SQL best practices
• Optimizing queries using indexes
• Creating analytical SQL views for BI reporting
• Connecting PostgreSQL with Power BI using DirectQuery
• Building business metrics like Revenue, Orders, Customers and AOV
• Understanding how data analysts build reporting systems
• Designing a complete analytics workflow from database to insights

⏱️ Timestamps

00:00:00 - 00:25:21 Introduction to Industry-Level Data Analytics Project
00:25:21 - 00:56:44 PostgreSQL Database Setup and Data Operations
00:56:44 - 01:05:29 Power BI Data Connectivity and Storage Modes Explained
01:05:29 - 01:22:57 Power BI Setup, Data Modeling and DAX Measures
01:22:57 - 01:43:57 Power BI Report View 1 – Business Overview Dashboard
01:43:57 - 02:04:06 Power BI Report View 2 – Sales, Products and Category Analysis
02:04:06 - 02:32:23 Power BI Report View 3 – Customer Growth, Delivery, Logistics and Reviews Analysis
02:32:23 - 02:59:18 Power BI Report View 4 – Payments, Sellers and Drill Through Analysis
02:59:18 - 03:02:16 Final Insights and Project Wrap Up
03:02:16 - END Outro

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more Data Analytics, SQL, and AI learning, and COMMENT 💬 below if you have any questions or topic suggestions.

data analytics project , postgresql project , power bi project , data analytics tutorial , sql project for beginners , postgresql tutorial , power bi tutorial , end to end data analytics project , industry level data analytics project , data analytics portfolio project , power bi dashboard project , sql power bi project , data analyst project tutorial , postgresql power bi integration , sql data analysis , data analytics course , data analysis project]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306222Mon, 09 Mar 2026 15:21:52 +0000fertIn this complete Industry-Level Data Analytics Project, you will learn how to build a real-world analytics workflow using PostgreSQL and Power BI. This session focuses on building a full end-to-end data analytics project, starting from raw dataset...
This session focuses on building a full end-to-end data analytics project, starting from raw dataset ingestion in PostgreSQL to creating optimized analytical views and finally connecting the database with Power BI to perform business analysis and build powerful data insights.

Whether you are a Data Analytics beginner, SQL learner, or someone preparing portfolio projects, this session will help you understand how real analytics systems are structured and how data analysts work with databases and BI tools in the industry.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

💻 Project Files
https://drive.google.com/drive/folders/1XEyJDvVJdy8WaOBQjempuzpuW7dV-Pxw?usp=drive_link

📚 What You Will Learn in This Video

• Understanding the structure of a real-world e-commerce dataset
• Setting up PostgreSQL database for analytics workflows
• Creating tables and importing large CSV datasets
• Data validation, cleaning and SQL best practices
• Optimizing queries using indexes
• Creating analytical SQL views for BI reporting
• Connecting PostgreSQL with Power BI using DirectQuery
• Building business metrics like Revenue, Orders, Customers and AOV
• Understanding how data analysts build reporting systems
• Designing a complete analytics workflow from database to insights

⏱️ Timestamps

00:00:00 - 00:25:21 Introduction to Industry-Level Data Analytics Project
00:25:21 - 00:56:44 PostgreSQL Database Setup and Data Operations
00:56:44 - 01:05:29 Power BI Data Connectivity and Storage Modes Explained
01:05:29 - 01:22:57 Power BI Setup, Data Modeling and DAX Measures
01:22:57 - 01:43:57 Power BI Report View 1 – Business Overview Dashboard
01:43:57 - 02:04:06 Power BI Report View 2 – Sales, Products and Category Analysis
02:04:06 - 02:32:23 Power BI Report View 3 – Customer Growth, Delivery, Logistics and Reviews Analysis
02:32:23 - 02:59:18 Power BI Report View 4 – Payments, Sellers and Drill Through Analysis
02:59:18 - 03:02:16 Final Insights and Project Wrap Up
03:02:16 - END Outro

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more Data Analytics, SQL, and AI learning, and COMMENT 💬 below if you have any questions or topic suggestions.

data analytics project , postgresql project , power bi project , data analytics tutorial , sql project for beginners , postgresql tutorial , power bi tutorial , end to end data analytics project , industry level data analytics project , data analytics portfolio project , power bi dashboard project , sql power bi project , data analyst project tutorial , postgresql power bi integration , sql data analysis , data analytics course , data analysis project]]>10937falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883280
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306203Wed, 04 Mar 2026 04:56:04 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>3676falsefullhttps://www.spreaker.com/episode/generative-ai-full-course-part-1-beginner-to-advanced-langchain-llms-prompt-engineering--74883333
This is Part 1 of our complete Generative AI series, where we focus on the core fundamentals required before moving to advanced topics like RAG and production-level AI systems.
Whether you are a beginner or an aspiring AI developer, this session will help you understand how real AI applications are built from scratch.

👨‍🏫 Instructor – Akarsh Vyas guiding you step-by-step through the core building blocks of Generative AI in a clear and practical way.

📚 What You Will Learn in This Video

• What is Generative AI and how it works
• Understanding Large Language Models (LLMs)
• How to use APIs to access AI models
• Writing effective prompts
• Structured Input vs Structured Output
• Generating clean structured data using schemas
• Prompt Templates and dynamic prompts
• How LangChain connects everything together
• How real-world AI applications are structured

📝 Notes -
https://drive.google.com/file/d/1ocrLutqXnGfRVDglowbtIPguebAAnxmu/view?usp=sharing

Code -
https://github.com/AkarshVyas/GenAI-Youtube-1

⏱️ Timestamps -
00:00:00 - 00:01:02 Introduction to Generative AI Chatbot Project
00:01:02 - 00:03:53 Prerequisites for Building AI Chatbot
00:03:53 - 00:11:08 Project Phases & Development Roadmap
00:11:08 - 00:35:27 Foundation of LLM & Chat Models
00:35:27 - 00:41:02 Creating Python Virtual Environment
00:41:02 - 00:47:56 Basic Project Setup & Folder Structure
00:47:56 - 01:01:42 Getting API Keys (OpenAI & Other Providers)
01:01:42 - 01:07:46 Creating requirements.txt File
01:07:46 - 01:28:24 Using Chat Models in Python
01:28:24 - 01:44:27 Integrating Hugging Face Models
01:44:27 - 01:52:16 Running AI Models Locally
01:52:16 - 02:08:56 Understanding Embedding Models
02:08:56 - 02:21:29 Building a Basic AI Chatbot
02:21:29 - 02:35:51 Working with Messages & Conversations
02:35:51 - 02:45:04 Creating Chatbot UI & Exploration
02:45:04 - 02:55:32 Completing the AI Project
02:55:32 - 03:26:03 Prompt Templates (CineSage AI Project)
03:26:03 - 03:50:54 Structured Output & Final CineSage Completion
03:50:54 - END Outro

🌐 Connect With Sheryians

🌐 Connect With Sheryians - https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.


generative ai full course , generative ai tutorial , langchain tutorial , llm tutorial , prompt engineering tutorial , master generative ai , generative ai 2026 , ai full course for beginners , langchain course , large language models explained , structured output in ai , prompt templates tutorial , gen ai project , ai development course ,]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306180Mon, 02 Mar 2026 15:00:42 +0000fertIn this 4-hour complete Generative AI full course, you will build a strong foundation in modern AI development using LangChain and Large Language Models. This is Part 1 of our complete Generative AI series, where we focus on the core fundamentals...
This is Part 1 of our complete Generative AI series, where we focus on the core fundamentals required before moving to advanced topics like RAG and production-level AI systems.
Whether you are a beginner or an aspiring AI developer, this session will help you understand how real AI applications are built from scratch.

👨‍🏫 Instructor – Akarsh Vyas guiding you step-by-step through the core building blocks of Generative AI in a clear and practical way.

📚 What You Will Learn in This Video

• What is Generative AI and how it works
• Understanding Large Language Models (LLMs)
• How to use APIs to access AI models
• Writing effective prompts
• Structured Input vs Structured Output
• Generating clean structured data using schemas
• Prompt Templates and dynamic prompts
• How LangChain connects everything together
• How real-world AI applications are structured

📝 Notes -
https://drive.google.com/file/d/1ocrLutqXnGfRVDglowbtIPguebAAnxmu/view?usp=sharing

Code -
https://github.com/AkarshVyas/GenAI-Youtube-1

⏱️ Timestamps -
00:00:00 - 00:01:02 Introduction to Generative AI Chatbot Project
00:01:02 - 00:03:53 Prerequisites for Building AI Chatbot
00:03:53 - 00:11:08 Project Phases & Development Roadmap
00:11:08 - 00:35:27 Foundation of LLM & Chat Models
00:35:27 - 00:41:02 Creating Python Virtual Environment
00:41:02 - 00:47:56 Basic Project Setup & Folder Structure
00:47:56 - 01:01:42 Getting API Keys (OpenAI & Other Providers)
01:01:42 - 01:07:46 Creating requirements.txt File
01:07:46 - 01:28:24 Using Chat Models in Python
01:28:24 - 01:44:27 Integrating Hugging Face Models
01:44:27 - 01:52:16 Running AI Models Locally
01:52:16 - 02:08:56 Understanding Embedding Models
02:08:56 - 02:21:29 Building a Basic AI Chatbot
02:21:29 - 02:35:51 Working with Messages & Conversations
02:35:51 - 02:45:04 Creating Chatbot UI & Exploration
02:45:04 - 02:55:32 Completing the AI Project
02:55:32 - 03:26:03 Prompt Templates (CineSage AI Project)
03:26:03 - 03:50:54 Structured Output & Final CineSage Completion
03:50:54 - END Outro

🌐 Connect With Sheryians

🌐 Connect With Sheryians - https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.


generative ai full course , generative ai tutorial , langchain tutorial , llm tutorial , prompt engineering tutorial , master generative ai , generative ai 2026 , ai full course for beginners , langchain course , large language models explained , structured output in ai , prompt templates tutorial , gen ai project , ai development course ,]]>13927falsefullhttps://www.spreaker.com/episode/lets-talk-about-ml-ops--74883285https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306210Sat, 28 Feb 2026 05:40:35 +0000fertIn this live session, we’ll have an open Q&A where you can bring your real career doubts, confusion, and struggles whether it's about getting into tech, feeling stuck, or not knowing what to do next. Alongside that, we’ll also talk about MLOps...5611falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883322
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306204Thu, 26 Feb 2026 06:18:54 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>4851falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883317
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306226Tue, 24 Feb 2026 06:49:06 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>5111falsefullhttps://www.spreaker.com/episode/build-an-industry-level-taxi-fare-dashboard-in-power-bi-end-to-end-project--74883295
🎓 Instructor
Dhanesh Malviya
Co-Founder, Sheryians Coding School

Video Content - https://drive.google.com/drive/folders/1hcfPnvQBVwmwCN_WXcPFLRnLJP5MN1sQ?usp=sharing

⏱️ Timestamps

00:00:00 - 00:01:19 | Introduction
00:01:19 - 00:02:12 | Understanding the Dataset
00:02:12 - 00:05:29 | Loading Data into Power BI
00:05:29 - 00:14:13 | Homepage & Overall Dashboard
00:14:13 - 00:29:36 | Vehicle Type Analysis
00:29:36 - 00:35:27 | Revenue Analysis (Payment & Distance Distribution)
00:35:27 - 00:46:38 | Cancellation Analysis
00:46:38 - 00:53:59 | Ratings Dashboard Creation
00:53:59 - 00:57:26 | Creating Revenue_Tier Column
00:57:26 - 00:58:59 | Creating Revenue_per_KM Column
00:58:59 - 01:00:53 | Creating Payment_Category Column
01:00:53 - 01:03:40 | Creating Is_Peak_Hour Column
01:03:40 - 01:06:47 | Creating Driver_Performance_Category Column
01:06:47 - 01:09:27 | Creating Distance_Category Column
01:09:27 - 01:12:57 | Creating Days_Since_Last_Ride Column
01:12:57 - 01:15:17 | Creating Day_Part Column
01:15:17 - 01:20:01 | Creating Customer_Segment Column
01:20:01 - 01:22:36 | Summary Sheet
01:22:36 - 01:43:18 | Project Summary
01:43:18 - 01:45:26 | UI Design Improvements
01:45:26 - 01:46:05 | Homepage UI
01:46:05 - 01:47:20 | Overall Dashboard UI
01:47:20 - 01:52:23 | Vehicle Type UI
01:52:23 - 01:53:54 | Revenue Dashboard UI
01:53:54 - 02:03:19 | Cancellation UI
02:03:19 - 02:04:27 | Ratings UI
02:04:27 - 02:06:30 | Summary UI
02:06:30 - 02:10:56 | Publishing the Report
02:10:56 - End | Outro

🌐 Connect With Sheryians - https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.


Taxi Fare Analysis, Taxi Fare Analysis with Power BI, Power BI Project, Power BI Dashboard Project, Industry Level Power BI Project, Real World Power BI Project, Data Analytics Project, Business Intelligence Dashboard, Power BI End to End Project, Power BI for Beginners, Dhanesh Malviya, sheryians ai school]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306220Mon, 23 Feb 2026 14:30:41 +0000fertThis video showcases a real-world Taxi Fare Analysis project built in Power BI. From data cleaning to dashboard design, we cover every step required to create a stakeholder-ready business intelligence solution. The dashboard highlights key metrics...
🎓 Instructor
Dhanesh Malviya
Co-Founder, Sheryians Coding School

Video Content - https://drive.google.com/drive/folders/1hcfPnvQBVwmwCN_WXcPFLRnLJP5MN1sQ?usp=sharing

⏱️ Timestamps

00:00:00 - 00:01:19 | Introduction
00:01:19 - 00:02:12 | Understanding the Dataset
00:02:12 - 00:05:29 | Loading Data into Power BI
00:05:29 - 00:14:13 | Homepage & Overall Dashboard
00:14:13 - 00:29:36 | Vehicle Type Analysis
00:29:36 - 00:35:27 | Revenue Analysis (Payment & Distance Distribution)
00:35:27 - 00:46:38 | Cancellation Analysis
00:46:38 - 00:53:59 | Ratings Dashboard Creation
00:53:59 - 00:57:26 | Creating Revenue_Tier Column
00:57:26 - 00:58:59 | Creating Revenue_per_KM Column
00:58:59 - 01:00:53 | Creating Payment_Category Column
01:00:53 - 01:03:40 | Creating Is_Peak_Hour Column
01:03:40 - 01:06:47 | Creating Driver_Performance_Category Column
01:06:47 - 01:09:27 | Creating Distance_Category Column
01:09:27 - 01:12:57 | Creating Days_Since_Last_Ride Column
01:12:57 - 01:15:17 | Creating Day_Part Column
01:15:17 - 01:20:01 | Creating Customer_Segment Column
01:20:01 - 01:22:36 | Summary Sheet
01:22:36 - 01:43:18 | Project Summary
01:43:18 - 01:45:26 | UI Design Improvements
01:45:26 - 01:46:05 | Homepage UI
01:46:05 - 01:47:20 | Overall Dashboard UI
01:47:20 - 01:52:23 | Vehicle Type UI
01:52:23 - 01:53:54 | Revenue Dashboard UI
01:53:54 - 02:03:19 | Cancellation UI
02:03:19 - 02:04:27 | Ratings UI
02:04:27 - 02:06:30 | Summary UI
02:06:30 - 02:10:56 | Publishing the Report
02:10:56 - End | Outro

🌐 Connect With Sheryians - https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/sheryians


Don’t forget to LIKE 👍, SUBSCRIBE 🔔 for more AI & Data-focused learning, and COMMENT 💬 below if you have any questions or topic suggestions.


Taxi Fare Analysis, Taxi Fare Analysis with Power BI, Power BI Project, Power BI Dashboard Project, Industry Level Power BI Project, Real World Power BI Project, Data Analytics Project, Business Intelligence Dashboard, Power BI End to End Project, Power BI for Beginners, Dhanesh Malviya, sheryians ai school]]>7869falsefullhttps://www.spreaker.com/episode/deep-learning-complete-course-part-4-transformers-attention-mechanism-completely-explained--74883314Understand attention, self-attention, and encoder-decoder models with clear intuition.
See how models process long sequences and generate text step-by-step.
A must-watch to strengthen your Deep Learning foundations.

🎯 Here’s What You’ll Learn in Deep Learning Part 4:

• Why RNNs and LSTMs struggle with long sequences
• The intuition behind the Attention mechanism
• Self-Attention explained step-by-step
• Query, Key, Value — what they actually mean
• How attention scores are calculated (with examples)
• Multi-Head Attention — why multiple heads exist
• Masked Attention and why models cannot see the future
• Encoder architecture — building contextual understanding
• Decoder architecture — generating sequences step by step
• Cross-Attention — how translation really works
• Feed Forward Networks inside Transformers
• Full Transformer architecture explained simply

📌 Timestamps –

00:00:00 – Introduction to Transformers & Deep Learning Concepts
00:02:11 – Quick Recap: CNN vs RNN vs ANN Explained
00:08:20 – What You Will Learn in This Complete Transformer Tutorial
00:10:20 – Encoder and Decoder Architecture Explained
00:59:41 – Attention Mechanism in Deep Learning
01:29:39 – Introduction to Transformers Architecture
01:43:11 – Multi-Head Attention Layer Explained
02:28:03 – Multi-Head Attention Summary & Intuition
02:34:20 – Before Learning Feed Forward Neural Networks (Important Concepts)
02:42:24 – Positional Encoding Explained with Intuition
02:51:05 – Feed Forward Neural Network inside Transformers
03:01:46 – Transformers Training & Testing Process
03:48:51 – Generative AI Announcement
03:49:20 – Outro & Final Thoughts


📘 Notes
https://drive.google.com/file/d/1j530XBAcZBMCCfHospM829jwtIES3Tkb/view?usp=sharing

🌐 Visit Our Website:
https://sheryians.com/

🌐 Explore Our Courses:
https://sheryians.com/courses

📷 Instagram
https://www.instagram.com/sheryians.ai

deep learning complete course, transformers explained, transformer architecture, self attention mechanism, multi head attention, encoder decoder model, artificial intelligence course, machine learning tutorial, large language models, gpt architecture explained, nlp transformers, ai full course 2026, learn deep learning, aakarsh vyas ai]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306202Mon, 16 Feb 2026 14:30:06 +0000fertIn this video, we explore Transformers — the architecture behind modern AI and Large Language Models. Understand attention, self-attention, and encoder-decoder models with clear intuition. See how models process long sequences and generate text...Understand attention, self-attention, and encoder-decoder models with clear intuition.
See how models process long sequences and generate text step-by-step.
A must-watch to strengthen your Deep Learning foundations.

🎯 Here’s What You’ll Learn in Deep Learning Part 4:

• Why RNNs and LSTMs struggle with long sequences
• The intuition behind the Attention mechanism
• Self-Attention explained step-by-step
• Query, Key, Value — what they actually mean
• How attention scores are calculated (with examples)
• Multi-Head Attention — why multiple heads exist
• Masked Attention and why models cannot see the future
• Encoder architecture — building contextual understanding
• Decoder architecture — generating sequences step by step
• Cross-Attention — how translation really works
• Feed Forward Networks inside Transformers
• Full Transformer architecture explained simply

📌 Timestamps –

00:00:00 – Introduction to Transformers & Deep Learning Concepts
00:02:11 – Quick Recap: CNN vs RNN vs ANN Explained
00:08:20 – What You Will Learn in This Complete Transformer Tutorial
00:10:20 – Encoder and Decoder Architecture Explained
00:59:41 – Attention Mechanism in Deep Learning
01:29:39 – Introduction to Transformers Architecture
01:43:11 – Multi-Head Attention Layer Explained
02:28:03 – Multi-Head Attention Summary & Intuition
02:34:20 – Before Learning Feed Forward Neural Networks (Important Concepts)
02:42:24 – Positional Encoding Explained with Intuition
02:51:05 – Feed Forward Neural Network inside Transformers
03:01:46 – Transformers Training & Testing Process
03:48:51 – Generative AI Announcement
03:49:20 – Outro & Final Thoughts


📘 Notes
https://drive.google.com/file/d/1j530XBAcZBMCCfHospM829jwtIES3Tkb/view?usp=sharing

🌐 Visit Our Website:
https://sheryians.com/

🌐 Explore Our Courses:
https://sheryians.com/courses

📷 Instagram
https://www.instagram.com/sheryians.ai

deep learning complete course, transformers explained, transformer architecture, self attention mechanism, multi head attention, encoder decoder model, artificial intelligence course, machine learning tutorial, large language models, gpt architecture explained, nlp transformers, ai full course 2026, learn deep learning, aakarsh vyas ai]]>13907falsefullhttps://www.spreaker.com/episode/end-to-end-movie-recommendation-system-using-nlp-tf-idf-fastapi--74883330
All code files - https://github.com/master-temp/movie-rec

course link - https://www.sheryians.com/courses/courses-details/Data%20Science%20and%20Analytics%20with%20GenAI

Welcome to a real-world end-to-end Machine Learning project!
In this project, we build and deploy a content-based movie recommendation system from scratch using Natural Language Processing (NLP) techniques.

You’ll learn how recommendation engines actually work behind platforms like Netflix and Prime Video and how to deploy them using FastAPI as a production-ready backend.

00:00:00 - 00:01:34 - Introduction
00:01:34 - 00:28:43 - Data Gathering and cleaning
00:28:43 - 00:42:56 - NLP Text preprocessing
00:42:56 - 00:56:31 - Text Vectorization
00:56:31 - 01:07:04 - What is cosine similarity
01:07:04 - 01:18:04 - Testing and making the pickle file
01:18:04 - 02:07:34 - Making API and UI
02:07:34 - 02:09:05 - Outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306217Mon, 05 Jan 2026 15:30:19 +0000fertInstructor – Akarsh Vyas & Dhanesh Malviya All code files - https://github.com/master-temp/movie-rec course link - https://www.sheryians.com/courses/courses-details/Data%20Science%20and%20Analytics%20with%20GenAI Welcome to a real-world...
All code files - https://github.com/master-temp/movie-rec

course link - https://www.sheryians.com/courses/courses-details/Data%20Science%20and%20Analytics%20with%20GenAI

Welcome to a real-world end-to-end Machine Learning project!
In this project, we build and deploy a content-based movie recommendation system from scratch using Natural Language Processing (NLP) techniques.

You’ll learn how recommendation engines actually work behind platforms like Netflix and Prime Video and how to deploy them using FastAPI as a production-ready backend.

00:00:00 - 00:01:34 - Introduction
00:01:34 - 00:28:43 - Data Gathering and cleaning
00:28:43 - 00:42:56 - NLP Text preprocessing
00:42:56 - 00:56:31 - Text Vectorization
00:56:31 - 01:07:04 - What is cosine similarity
01:07:04 - 01:18:04 - Testing and making the pickle file
01:18:04 - 02:07:34 - Making API and UI
02:07:34 - 02:09:05 - Outro]]>7683falsefullhttps://www.spreaker.com/episode/fastapi-full-course-for-beginners-build-real-world-apis-ml-project-deployment--74883343
This tutorial is designed to help you understand how modern APIs are built in real projects using FastAPI, and how machine learning models can be deployed as production APIs.
We start from the fundamentals of FastAPI and gradually move toward building a complete backend application. To keep the learning beginner-friendly, the project uses a local JSON database where we implement full CRUD operations, request validation, and a clean API structure.
Once the backend foundation is clear, we integrate a Machine Learning model to build a Car Price Prediction API. The trained ML model is exposed through FastAPI endpoints and connected with a Streamlit frontend, demonstrating how backend, ML, and UI interact in a real application workflow.

Finally, we deploy the full project so you understand how real systems go live in production.

By the end of this tutorial, you will understand how to structure FastAPI projects, deploy ML models through APIs, and build a complete backend workflow from development to deployment.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

💻 Project Files
https://drive.google.com/file/d/1TLjZTj4z8QSbBXX2ew4cavlJyL6TmLUv/view?usp=sharing

📚 What You Will Learn in This Video

• FastAPI fundamentals and project setup
• Understanding API architecture used in real backend systems
• Structuring FastAPI projects for scalability
• Request and response validation using Pydantic
• CRUD operations using a local JSON database
• Proper API error handling and status codes
• Integrating Machine Learning models with FastAPI
• Building a Car Price Prediction API
• Creating a frontend application using Streamlit
• Connecting Backend, ML model and UI together
• Deploying FastAPI backend on Render
• Deploying Streamlit application on Streamlit Cloud
• Understanding how backend APIs power ML applications

Timestamps -
00:00 - 01:57 Introduction: Welcome and course overview
01:57 - 04:40 What is an API? Understanding why APIs are essential
04:40 - 06:23 Monolithic vs Microservices Architecture
06:23 - 08:01 Why FastAPI? Comparison with Django and Flask
08:01 - 08:42 Core Components: Pydantic and Starlette overview
08:42 - 01:12:43 HTTP Protocols: Understanding request–response cycles
01:12:43 - 01:13:30 Installation: Setting up FastAPI, Uvicorn, and Pydantic
01:13:30 - 01:15:37 Project Structure: Creating a production-ready folder structure
01:15:37 - 01:19:19 First Route: Building your first "Hello World" endpoint
01:19:19 - 01:23:27 HTTP Methods (CRUD): GET, POST, PUT, DELETE explained
01:23:27 - 01:31:04 Static vs Dynamic Routes: Handling path parameters
01:31:04 - 01:36:35 Query Parameters: Implementing search filters and sorting
01:36:35 - 01:46:15 HTTP Status Codes: Understanding 2xx, 4xx, and 5xx responses
01:46:15 - 01:51:50 Exception Handling: Using HTTPException for error responses
01:51:50 - 01:17:41 Pagination: Managing large datasets efficiently
01:17:41 - 01:21:44 Introduction to Pydantic: Why data validation matters
01:21:44 - 01:24:21 Field Validation: Using Annotated and Field
01:24:21 - 01:33:36 Nested Models: Handling complex data structures
01:33:36 - 01:45:19 Custom Validators: Using @field_validator and @model_validator
01:45:19 - 02:00:50 Computed Fields: Calculating values dynamically
02:00:50 - 02:49:20 Implementing CRUD Operations: Building full backend logic
02:49:20 - 02:56:23 Response Models: Controlling and formatting API output
02:56:23 - 03:14:39 Dependency Injection: Reusing logic across endpoints
03:14:39 - 03:34:39 ML Model Integration: Car Price Prediction API
03:34:39 - 03:41:24 Streamlit Frontend: Building the user interface
03:41:24 - END Deployment: Deploying backend on Render and frontend on Streamlit Cloud

🌐 Connect With Sheryians

🌐 Official Website – https://sheryians.com/

🔗 View Our Courses – https://www.sheryians.com/courses/68d
📷 Instagram – https://www.instagram.com/sheryians.ai
🎮 Discord – https://discord.gg/HFH2V54WZ

Don’t forget to LIKE 👍, SUBSCRIBE 🔔 and SHARE if this tutorial helped you learn FastAPI, backend development, and ML deployment.

fastapi tutorial , fastapi project , fastapi machine learning project , fastapi ml deployment , fastapi backend tutorial , python fastapi tutorial , fastapi crud api , fastapi streamlit project , fastapi deployment tutorial , fastapi render deployment , machine learning api tutorial , ml model deployment fastapi , python backend project , fastapi for beginners , backend development python , streamlit fastapi project , car price prediction api , data science fastapi project , fastapi production api]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306205Tue, 30 Dec 2025 15:01:08 +0000fertIn this complete FastAPI + Machine Learning Project, you will learn how to build a real-world backend system and deploy it with a working frontend interface. This tutorial is designed to help you understand how modern APIs are built in real projects...
This tutorial is designed to help you understand how modern APIs are built in real projects using FastAPI, and how machine learning models can be deployed as production APIs.
We start from the fundamentals of FastAPI and gradually move toward building a complete backend application. To keep the learning beginner-friendly, the project uses a local JSON database where we implement full CRUD operations, request validation, and a clean API structure.
Once the backend foundation is clear, we integrate a Machine Learning model to build a Car Price Prediction API. The trained ML model is exposed through FastAPI endpoints and connected with a Streamlit frontend, demonstrating how backend, ML, and UI interact in a real application workflow.

Finally, we deploy the full project so you understand how real systems go live in production.

By the end of this tutorial, you will understand how to structure FastAPI projects, deploy ML models through APIs, and build a complete backend workflow from development to deployment.

👨‍🏫 Instructor – Dhanesh Malviya
(Co-Founder, Sheryians Coding School)

💻 Project Files
https://drive.google.com/file/d/1TLjZTj4z8QSbBXX2ew4cavlJyL6TmLUv/view?usp=sharing

📚 What You Will Learn in This Video

• FastAPI fundamentals and project setup
• Understanding API architecture used in real backend systems
• Structuring FastAPI projects for scalability
• Request and response validation using Pydantic
• CRUD operations using a local JSON database
• Proper API error handling and status codes
• Integrating Machine Learning models with FastAPI
• Building a Car Price Prediction API
• Creating a frontend application using Streamlit
• Connecting Backend, ML model and UI together
• Deploying FastAPI backend on Render
• Deploying Streamlit application on Streamlit Cloud
• Understanding how backend APIs power ML applications

Timestamps -
00:00 - 01:57 Introduction: Welcome and course overview
01:57 - 04:40 What is an API? Understanding why APIs are essential
04:40 - 06:23 Monolithic vs Microservices Architecture
06:23 - 08:01 Why FastAPI? Comparison with Django and Flask
08:01 - 08:42 Core Components: Pydantic and Starlette overview
08:42 - 01:12:43 HTTP Protocols: Understanding request–response cycles
01:12:43 - 01:13:30 Installation: Setting up FastAPI, Uvicorn, and Pydantic
01:13:30 - 01:15:37 Project Structure: Creating a production-ready folder structure
01:15:37 - 01:19:19 First Route: Building your first "Hello World" endpoint
01:19:19 - 01:23:27 HTTP Methods (CRUD): GET, POST, PUT, DELETE explained
01:23:27 - 01:31:04 Static vs Dynamic Routes: Handling path parameters
01:31:04 - 01:36:35 Query Parameters: Implementing search filters and sorting
01:36:35 - 01:46:15 HTTP Status Codes: Understanding 2xx, 4xx, and 5xx responses
01:46:15 - 01:51:50 Exception Handling: Using HTTPException for error responses
01:51:50 - 01:17:41 Pagination: Managing large datasets efficiently
01:17:41 - 01:21:44 Introduction to Pydantic: Why data validation matters
01:21:44 - 01:24:21 Field Validation: Using Annotated and Field
01:24:21 - 01:33:36 Nested Models: Handling complex data structures
01:33:36 - 01:45:19 Custom Validators: Using @field_validator and @model_validator
01:45:19 - 02:00:50 Computed Fields: Calculating values dynamically
02:00:50 - 02:49:20 Implementing CRUD Operations: Building full backend logic
02:49:20 - 02:56:23 Response Models: Controlling and formatting API output
02:56:23 - 03:14:39 Dependency Injection: Reusing logic...]]>14064falsefullhttps://www.spreaker.com/episode/deep-learning-complete-course-part-3-rnn-implementation--74883315
Welcome back!
In this video, we take the next step in Deep Learning and dive into Recurrent Neural Networks (RNNs) the models that allow neural networks to understand sequential and time-based data.

After mastering ANN and CNN, this session completes a crucial part of Deep Learning by introducing architectures designed for memory, context, and sequence learning.

You can download the code and datasets from here:
Code files and Dataset – https://github.com/AkarshVyas/Next_word_prediction

All the notes of our classes are here:
Notes – https://drive.google.com/file/d/1Cykev1PzEEMmU3Unif_HBxKtrZUwzgB8/view?usp=sharing

Check out our course - https://www.sheryians.com/courses/courses-details/Data%20Science%20and%20Analytics%20with%20GenAI

Here’s what you’ll learn in this Deep Learning Part 3:

Why ANNs and CNNs fail on sequential data

Introduction to Recurrent Neural Networks (RNNs) and how they work

Understanding vanishing and exploding gradient problems

LSTM (Long Short-Term Memory) — gates, memory cells, and intuition

GRU (Gated Recurrent Units) and how they differ from LSTMs

Comparison between RNN vs LSTM vs GRU

Step-by-step architecture explanation with real examples

Hands-on projects using RNN, LSTM, and GRU

Implementing sequence models using TensorFlow / Keras]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306218Mon, 22 Dec 2025 14:00:02 +0000fertInstructor – Akarsh Vyas Welcome back! In this video, we take the next step in Deep Learning and dive into Recurrent Neural Networks (RNNs) the models that allow neural networks to understand sequential and time-based data. After mastering ANN and...
Welcome back!
In this video, we take the next step in Deep Learning and dive into Recurrent Neural Networks (RNNs) the models that allow neural networks to understand sequential and time-based data.

After mastering ANN and CNN, this session completes a crucial part of Deep Learning by introducing architectures designed for memory, context, and sequence learning.

You can download the code and datasets from here:
Code files and Dataset – https://github.com/AkarshVyas/Next_word_prediction

All the notes of our classes are here:
Notes – https://drive.google.com/file/d/1Cykev1PzEEMmU3Unif_HBxKtrZUwzgB8/view?usp=sharing

Check out our course - https://www.sheryians.com/courses/courses-details/Data%20Science%20and%20Analytics%20with%20GenAI

Here’s what you’ll learn in this Deep Learning Part 3:

Why ANNs and CNNs fail on sequential data

Introduction to Recurrent Neural Networks (RNNs) and how they work

Understanding vanishing and exploding gradient problems

LSTM (Long Short-Term Memory) — gates, memory cells, and intuition

GRU (Gated Recurrent Units) and how they differ from LSTMs

Comparison between RNN vs LSTM vs GRU

Step-by-step architecture explanation with real examples

Hands-on projects using RNN, LSTM, and GRU

Implementing sequence models using TensorFlow / Keras]]>14574falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883313
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303128336306213Tue, 11 Nov 2025 04:46:21 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>3346falsefullhttps://www.spreaker.com/episode/how-to-crack-your-first-internship-job--74883307
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677965Fri, 07 Nov 2025 04:44:46 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>5596falsefullhttps://www.spreaker.com/episode/lets-talk-about-job-opportunities-and-market--74883331
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept this is your chance to ask your questions LIVE and get them solved instantly.

And today lets discuss about Jobs]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677974Wed, 05 Nov 2025 16:19:16 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept this is your chance to ask your questions LIVE and get them solved instantly.

And today lets discuss about Jobs]]>3661falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-baat-cheet-session--74883316
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678040Wed, 05 Nov 2025 04:12:26 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>4011falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883302
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677979Tue, 04 Nov 2025 04:40:40 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>4056falsefullhttps://www.spreaker.com/episode/data-science-and-analytics-with-generative-ai-launch--74883327
In this live session, we’ll cover:
What this course includes (from Python to AI)
How you’ll learn Data Science, Machine Learning & Generative AI step-by-step
Real projects, hands-on coding, and career roadmap
Surprise launch offers & Q&A session!

If you’ve ever dreamed of becoming a Data Scientist, AI Engineer, or GenAI Expert, this is where your journey begins!]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677973Sat, 01 Nov 2025 16:55:09 +0000fertGet ready for the official launch of our Data Science and Analytics with Generative AI Course — the most complete and practical program you’ll ever find! In this live session, we’ll cover: What this course includes (from Python to AI) How you’ll...
In this live session, we’ll cover:
What this course includes (from Python to AI)
How you’ll learn Data Science, Machine Learning & Generative AI step-by-step
Real projects, hands-on coding, and career roadmap
Surprise launch offers & Q&A session!

If you’ve ever dreamed of becoming a Data Scientist, AI Engineer, or GenAI Expert, this is where your journey begins!]]>4326falsefullhttps://www.spreaker.com/episode/data-science-analytics-gen-ai-launch-your-ai-career-now--74883310
Use Coupon: "YT15" for 15% discount.

Welcome to the Ultimate Data Science and Generative AI Course.

This is not just another course. It’s a complete journey from beginner to pro, where you’ll learn everything you need to become a Data Scientist, Analyst, and AI Expert in 2025.

What You’ll Learn Inside:
You’ll start with Python programming, moving from basics to advanced concepts.
You’ll understand Statistics, Probability, and Hypothesis Testing.
You’ll master NumPy, Pandas, and Data Visualization using Matplotlib and Seaborn.
You’ll explore Excel Intelligence and Power BI for Business Analytics.
You’ll learn SQL for data handling and querying.
You’ll build real Machine Learning and Deep Learning projects.
You’ll dive deep into Generative AI with LangChain, RAG, AI Agents, and Vector Databases.
Finally, you’ll gain practical experience in MLOps with MLFlow, Docker, CI/CD, and Model Deployment.

Why This Course Is Different:
Most data science courses stop after Machine Learning. This course takes you further by integrating Generative AI and MLOps, helping you become a complete AI Engineer.
Every topic is taught through hands-on examples, real projects, and industry-level guidance from developers and data scientists.

Who This Course Is For:
College students who want to start their AI journey
Working professionals looking to switch into Data Science
Anyone who wants to future-proof their career with AI skills

Join the live launch and take the first step toward becoming a Data Scientist with the power of Generative AI.

Subscribe and set a reminder so you don’t miss the live session.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678011Sat, 01 Nov 2025 15:18:25 +0000fertCourse Link: https://sheryians.com/courses/courses-details/course-id/68da779296b89547293c7a26?utm_source=youtube&utm_medium=trailer&utm_campaign=trailer_1 Use Coupon: "YT15" for 15% discount. Welcome to the Ultimate Data Science and...
Use Coupon: "YT15" for 15% discount.

Welcome to the Ultimate Data Science and Generative AI Course.

This is not just another course. It’s a complete journey from beginner to pro, where you’ll learn everything you need to become a Data Scientist, Analyst, and AI Expert in 2025.

What You’ll Learn Inside:
You’ll start with Python programming, moving from basics to advanced concepts.
You’ll understand Statistics, Probability, and Hypothesis Testing.
You’ll master NumPy, Pandas, and Data Visualization using Matplotlib and Seaborn.
You’ll explore Excel Intelligence and Power BI for Business Analytics.
You’ll learn SQL for data handling and querying.
You’ll build real Machine Learning and Deep Learning projects.
You’ll dive deep into Generative AI with LangChain, RAG, AI Agents, and Vector Databases.
Finally, you’ll gain practical experience in MLOps with MLFlow, Docker, CI/CD, and Model Deployment.

Why This Course Is Different:
Most data science courses stop after Machine Learning. This course takes you further by integrating Generative AI and MLOps, helping you become a complete AI Engineer.
Every topic is taught through hands-on examples, real projects, and industry-level guidance from developers and data scientists.

Who This Course Is For:
College students who want to start their AI journey
Working professionals looking to switch into Data Science
Anyone who wants to future-proof their career with AI skills

Join the live launch and take the first step toward becoming a Data Scientist with the power of Generative AI.

Subscribe and set a reminder so you don’t miss the live session.]]>211falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883308
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677955Wed, 29 Oct 2025 04:40:54 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>3441falsefullhttps://www.spreaker.com/episode/the-ml-workflow-that-you-must-know--74883312instagram - https://www.instagram.com/sheryians.ai?igsh=aG9mcDk0cDZ5M29p
Master the Complete Machine Learning Workflow in One Video!
From collecting data to deploying models this video covers every step you must know to become a real-world Machine Learning Engineer.

Whether you're a beginner starting your ML journey or a developer planning to work on AI projects…
This video will give you the exact blueprint professionals use in top companies.

What You’ll Learn:

Problem Definition
Data Collection
Exploratory Data Analysis (EDA)
Data Cleaning & Preprocessing
Train-Test Split
Choosing the Right Model
Model Training
Evaluation Metrics (MSE, R², Accuracy, etc.)
Hyperparameter Tuning

By the end of this video, you will be able to plan, build, evaluate, and deliver an end-to-end ML project confidently!]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678041Mon, 27 Oct 2025 14:00:19 +0000fertInstructor in this video - Akarsh vyas instagram - https://www.instagram.com/sheryians.ai?igsh=aG9mcDk0cDZ5M29p Master the Complete Machine Learning Workflow in One Video! From collecting data to deploying models this video covers every step you must...instagram - https://www.instagram.com/sheryians.ai?igsh=aG9mcDk0cDZ5M29p
Master the Complete Machine Learning Workflow in One Video!
From collecting data to deploying models this video covers every step you must know to become a real-world Machine Learning Engineer.

Whether you're a beginner starting your ML journey or a developer planning to work on AI projects…
This video will give you the exact blueprint professionals use in top companies.

What You’ll Learn:

Problem Definition
Data Collection
Exploratory Data Analysis (EDA)
Data Cleaning & Preprocessing
Train-Test Split
Choosing the Right Model
Model Training
Evaluation Metrics (MSE, R², Accuracy, etc.)
Hyperparameter Tuning

By the end of this video, you will be able to plan, build, evaluate, and deliver an end-to-end ML project confidently!]]>1452falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883332
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677994Sun, 12 Oct 2025 05:37:14 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>4066falsefullhttps://www.spreaker.com/episode/sheryians-ai-live-qna-session--74883356
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678006Fri, 10 Oct 2025 17:13:26 +0000fertAsk Me Anything about AI, Machine Learning, and Data Science! Hey everyone! I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to...
Hey everyone!
I’m going LIVE to answer all your doubts about Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Python, and more! Whether you’re a beginner trying to get started or an advanced learner stuck on a concept — this is your chance to ask your questions LIVE and get them solved instantly.]]>3396falsefullhttps://www.spreaker.com/episode/deep-learning-complete-course-part-2-cnn-implementation--74883300Welcome back! In this video, we’ll take the next big step in Deep Learning and dive deep into Convolutional Neural Networks (CNNs) the architecture that completely changed the world of Computer Vision.

You can download the code and datasets from here:
Code Link – https://github.com/AkarshVyas/CNN-video

📘 All the notes of our classes are here:
Notes – https://drive.google.com/file/d/15b8U3Zo3WO-v9J93Is_h2ce7WVfC5ar9/view?usp=drive_link

Here’s what you’ll learn in this CNN deep dive:

The problem with ANN on images and why CNN was invented

The intuition behind Convolutions, Filters, and Feature Maps

Pooling layers and why they make CNNs efficient

Step-by-step architecture: Convolution → Pooling → Fully Connected

Famous CNN models (LeNet, AlexNet, VGG, ResNet) and how they shaped modern AI

Hands-on coding: Building CNNs with TensorFlow/Keras on real datasets

Applications of CNNs in real life — from face recognition to self-driving cars

These are the most important building blocks of modern Computer Vision. If you’ve understood ANNs from our first video, this session will complete the foundation you need before moving to advanced architectures and real-world AI projects.

By the end of this video, you’ll not only understand how CNNs work but also be able to build and train your own CNN from scratch.

0:00:00 - 00:00:38 - introduction
00:00:38 - 00:11:53- CNN(introduction)
00:11:55 - 00:19:00 - How CNN works
00:19:00 - 00:21:34 - Understanding the Architecture
00:21:34 - 00:25:03 - Layers in CNN
00:25:03 - 00:42:12 - Edge Finding in CNN
00:42:12 - 00:48:52 - understanding(padding and strides)
00:48:52 - 00:55:26 - why we use strides
00:55:26 - 01:04:41- pooling
01:04:41 - 01:06:47- max pooling
01:06:47 - 01:15:20 - Revision and flattening
01:15:20 - 01:54:13 - code implementation
01:54:13 - 01:54:47 - outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678048Mon, 08 Sep 2025 14:30:27 +0000fertInstructor – Akarsh Vyas Welcome back! In this video, we’ll take the next big step in Deep Learning and dive deep into Convolutional Neural Networks (CNNs) the architecture that completely changed the world of Computer Vision. You can download the...Welcome back! In this video, we’ll take the next big step in Deep Learning and dive deep into Convolutional Neural Networks (CNNs) the architecture that completely changed the world of Computer Vision.

You can download the code and datasets from here:
Code Link – https://github.com/AkarshVyas/CNN-video

📘 All the notes of our classes are here:
Notes – https://drive.google.com/file/d/15b8U3Zo3WO-v9J93Is_h2ce7WVfC5ar9/view?usp=drive_link

Here’s what you’ll learn in this CNN deep dive:

The problem with ANN on images and why CNN was invented

The intuition behind Convolutions, Filters, and Feature Maps

Pooling layers and why they make CNNs efficient

Step-by-step architecture: Convolution → Pooling → Fully Connected

Famous CNN models (LeNet, AlexNet, VGG, ResNet) and how they shaped modern AI

Hands-on coding: Building CNNs with TensorFlow/Keras on real datasets

Applications of CNNs in real life — from face recognition to self-driving cars

These are the most important building blocks of modern Computer Vision. If you’ve understood ANNs from our first video, this session will complete the foundation you need before moving to advanced architectures and real-world AI projects.

By the end of this video, you’ll not only understand how CNNs work but also be able to build and train your own CNN from scratch.

0:00:00 - 00:00:38 - introduction
00:00:38 - 00:11:53- CNN(introduction)
00:11:55 - 00:19:00 - How CNN works
00:19:00 - 00:21:34 - Understanding the Architecture
00:21:34 - 00:25:03 - Layers in CNN
00:25:03 - 00:42:12 - Edge Finding in CNN
00:42:12 - 00:48:52 - understanding(padding and strides)
00:48:52 - 00:55:26 - why we use strides
00:55:26 - 01:04:41- pooling
01:04:41 - 01:06:47- max pooling
01:06:47 - 01:15:20 - Revision and flattening
01:15:20 - 01:54:13 - code implementation
01:54:13 - 01:54:47 - outro]]>6888falsefullhttps://www.spreaker.com/episode/your-ai-ml-degrees-are-scam-disturbing-reality-of-tier-3-colleges--74883311
In this brutally honest video, I expose how 3rd-tier colleges thug students in the name of AI/ML:

Outdated syllabus that’s 80% same as CSE

Unqualified faculty with zero AI expertise

No proper labs or GPUs students rely on their own laptops

Fake promises of 20 LPA+ placements when reality is 3–4 LPA IT jobs

Selling hype instead of actual skill-building

We’ll also compare this with how IITs and NITs introduced AI branches properly with real infrastructure, qualified PhDs, and industry tie-ups.

If you’re in a 3rd-tier college, don’t worry in the second half I’ll also share how YOU can beat the system and still succeed in AI/ML through self-learning, projects, and networking.

Don’t fall for the scam. Watch till the end this video might just save your career.]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677993Wed, 03 Sep 2025 14:30:36 +0000fertColleges across India are selling students a dream with “Artificial Intelligence / Machine Learning / Data Science” branches… but the reality? It’s one of the biggest scams in education today. In this brutally honest video, I expose how 3rd-tier...
In this brutally honest video, I expose how 3rd-tier colleges thug students in the name of AI/ML:

Outdated syllabus that’s 80% same as CSE

Unqualified faculty with zero AI expertise

No proper labs or GPUs students rely on their own laptops

Fake promises of 20 LPA+ placements when reality is 3–4 LPA IT jobs

Selling hype instead of actual skill-building

We’ll also compare this with how IITs and NITs introduced AI branches properly with real infrastructure, qualified PhDs, and industry tie-ups.

If you’re in a 3rd-tier college, don’t worry in the second half I’ll also share how YOU can beat the system and still succeed in AI/ML through self-learning, projects, and networking.

Don’t fall for the scam. Watch till the end this video might just save your career.]]>799falsefullhttps://www.spreaker.com/episode/deep-learning-complete-course-part-1-ann-implementation--74883344📂 You can download the code and datasets from here:Code Link – https://github.com/AkarshVyas/Deep_learning_video
📘 All the notes of our classes are here:Notes – https://drive.google.com/file/d/1sZhNaqK428laMp_vhBhzZCpuSqELXhDM/view?usp=sharing

Here’s what you’ll learn:
* What Deep Learning really is (and how it differs from Machine Learning)
* The intuition behind Perceptrons & ANN
* Key building blocks: Activation Functions, Loss Functions, and Optimizers
* Forward Propagation explained step by step
* Backward Propagation with real intuition
* A quick hands-on demo project in TensorFlow/Keras
These are the most critical and often skipped steps in Deep Learning — but they are what make your neural networks actually work. Whether you’re just starting out or refreshing your basics, this session will give you the clarity you need for real-world AI projects.
🚀 Start here. Build smarter.


00:00:00 - 00:00:57 - Introduction
00:00:57 - 00:12:15 - Basics
00:12:15 - 00:29:53 - Perceptrons
00:29:53 - 00:48:54 - Forward Propogation
00:48:54 - 01:09:22 - Backward Propogation
01:09:22 - 01:23:55 - Vanishing Gradient Problem
01:23:55 - 01:50:48 - Activation Functions
01:50:48 - 02:20:11 - Basic Code for a Model
02:20:11 - 03:01:29 - Loss Functions
03:01:29 - 03:43:54 - Optimizers
03:43:54 - 04:16:25 - ANN Project
04:16:25 - 04:18:47 - Black Box vs White Box model
04:18:47 - 04:20:34 - Outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677969Mon, 25 Aug 2025 14:30:38 +0000fertInstructor – Akarsh VyasWelcome to the first step of your Deep Learning journey!In this video, we’ll dive into the complete foundation of neural networks, covering everything you must know before building your first ANN or CNN. 📂 You can download the...📂 You can download the code and datasets from here:Code Link – https://github.com/AkarshVyas/Deep_learning_video
📘 All the notes of our classes are here:Notes – https://drive.google.com/file/d/1sZhNaqK428laMp_vhBhzZCpuSqELXhDM/view?usp=sharing

Here’s what you’ll learn:
* What Deep Learning really is (and how it differs from Machine Learning)
* The intuition behind Perceptrons & ANN
* Key building blocks: Activation Functions, Loss Functions, and Optimizers
* Forward Propagation explained step by step
* Backward Propagation with real intuition
* A quick hands-on demo project in TensorFlow/Keras
These are the most critical and often skipped steps in Deep Learning — but they are what make your neural networks actually work. Whether you’re just starting out or refreshing your basics, this session will give you the clarity you need for real-world AI projects.
🚀 Start here. Build smarter.


00:00:00 - 00:00:57 - Introduction
00:00:57 - 00:12:15 - Basics
00:12:15 - 00:29:53 - Perceptrons
00:29:53 - 00:48:54 - Forward Propogation
00:48:54 - 01:09:22 - Backward Propogation
01:09:22 - 01:23:55 - Vanishing Gradient Problem
01:23:55 - 01:50:48 - Activation Functions
01:50:48 - 02:20:11 - Basic Code for a Model
02:20:11 - 03:01:29 - Loss Functions
03:01:29 - 03:43:54 - Optimizers
03:43:54 - 04:16:25 - ANN Project
04:16:25 - 04:18:47 - Black Box vs White Box model
04:18:47 - 04:20:34 - Outro]]>15635falsefullhttps://www.spreaker.com/episode/ultimate-data-science-roadmap-2025-180-days-step-by-step-schedule--74883305
The complete 6 months Roadmap - https://drive.google.com/file/d/1nljPerhfwzxpIiNUWOQ7gc1itX5OCkgj/view?usp=sharing

Want to become a Data Scientist but don’t know where to start? In this video, I’ll take you through a step-by-step roadmap from Beginner to Advanced, covering everything you need to land your first job in Data Science.

What you’ll learn in this video:
Python for Data Science (NumPy, Pandas, Matplotlib, Seaborn)
Statistics & Probability for Data Analysis
Data Cleaning, Preprocessing & Visualization
SQL for handling real-world data
Machine Learning Algorithms (Regression, Classification, Clustering)
Model Evaluation & Hyperparameter Tuning
Deep Learning (ANN, CNN, RNN with TensorFlow/Keras)
Specializations like NLP, Computer Vision, BI Tools & more

By the end of this roadmap, you’ll know exactly what to study, in what order, and how long it will take to become job-ready in Data Science.

Whether you’re a student, beginner, or career switcher, this roadmap will guide you to start learning and build projects that actually get you hired.

Don’t forget to Like, Share & Subscribe for more Data Science & AI tutorials!

#DataScience #Roadmap2025 #MachineLearning #DeepLearning #Python]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677990Mon, 18 Aug 2025 14:30:10 +0000fertThe Ultimate Data Science Roadmap (2025) The complete 6 months Roadmap - https://drive.google.com/file/d/1nljPerhfwzxpIiNUWOQ7gc1itX5OCkgj/view?usp=sharing Want to become a Data Scientist but don’t know where to start? In this video, I’ll take you...
The complete 6 months Roadmap - https://drive.google.com/file/d/1nljPerhfwzxpIiNUWOQ7gc1itX5OCkgj/view?usp=sharing

Want to become a Data Scientist but don’t know where to start? In this video, I’ll take you through a step-by-step roadmap from Beginner to Advanced, covering everything you need to land your first job in Data Science.

What you’ll learn in this video:
Python for Data Science (NumPy, Pandas, Matplotlib, Seaborn)
Statistics & Probability for Data Analysis
Data Cleaning, Preprocessing & Visualization
SQL for handling real-world data
Machine Learning Algorithms (Regression, Classification, Clustering)
Model Evaluation & Hyperparameter Tuning
Deep Learning (ANN, CNN, RNN with TensorFlow/Keras)
Specializations like NLP, Computer Vision, BI Tools & more

By the end of this roadmap, you’ll know exactly what to study, in what order, and how long it will take to become job-ready in Data Science.

Whether you’re a student, beginner, or career switcher, this roadmap will guide you to start learning and build projects that actually get you hired.

Don’t forget to Like, Share & Subscribe for more Data Science & AI tutorials!

#DataScience #Roadmap2025 #MachineLearning #DeepLearning #Python]]>1078falsefullhttps://www.spreaker.com/episode/leetcode-session-2-qna--74883319https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678012Fri, 15 Aug 2025 04:18:05 +0000fert3946falsefullhttps://www.spreaker.com/episode/leetcode-session-qna--74883324https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677963Tue, 05 Aug 2025 04:47:45 +0000fertIn this live session, I solved three exciting LeetCode problems — 2206: Divide Array Into Equal Pairs, 2357: Make Array Zero by Subtracting Equal Amounts, and 2210: Count Hills and Valleys in an Array. Along the way, we had a super interactive Q&A...4901falsefullhttps://www.spreaker.com/episode/learn-complete-nlp-with-project-bag-of-words-tf-idf-for-beginners--74883326In this video, we dive deep into Natural Language Processing (NLP) using Machine Learning – without touching deep learning!

Code and Data: https://github.com/AkarshVyas/NLP-content

Notes - https://drive.google.com/file/d/1tK_Za6gwhuf5FkIg-5kcQsnA09aS0k5y/view?usp=sharing

You’ll learn:

What is NLP and why it's important

Real-world applications of NLP

Full text preprocessing pipeline

Lowercasing, punctuation removal, emoji & stopword removal

Difference between TF-IDF and Bag of Words

Common ML techniques used in NLP

Hands-on Emotion Detection Project from scratch

Tools & Libraries used:

Python

Pandas, NLTK for text preprocessing

Scikit-learn for ML models (Naive Bayes, Logistic Regression)

CountVectorizer, TfidfVectorizer

Whether you're a beginner or a data science enthusiast, this video will teach you how to process text and build powerful ML models using simple NLP techniques.

Don’t forget to like, comment, and subscribe for more machine learning and AI content!]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678023Sat, 26 Jul 2025 14:01:29 +0000fertInstructor - Akarsh Vyas In this video, we dive deep into Natural Language Processing (NLP) using Machine Learning – without touching deep learning! Code and Data: https://github.com/AkarshVyas/NLP-content Notes -...In this video, we dive deep into Natural Language Processing (NLP) using Machine Learning – without touching deep learning!

Code and Data: https://github.com/AkarshVyas/NLP-content

Notes - https://drive.google.com/file/d/1tK_Za6gwhuf5FkIg-5kcQsnA09aS0k5y/view?usp=sharing

You’ll learn:

What is NLP and why it's important

Real-world applications of NLP

Full text preprocessing pipeline

Lowercasing, punctuation removal, emoji & stopword removal

Difference between TF-IDF and Bag of Words

Common ML techniques used in NLP

Hands-on Emotion Detection Project from scratch

Tools & Libraries used:

Python

Pandas, NLTK for text preprocessing

Scikit-learn for ML models (Naive Bayes, Logistic Regression)

CountVectorizer, TfidfVectorizer

Whether you're a beginner or a data science enthusiast, this video will teach you how to process text and build powerful ML models using simple NLP techniques.

Don’t forget to like, comment, and subscribe for more machine learning and AI content!]]>9015falsefullhttps://www.spreaker.com/episode/complete-sql-in-1-shot-for-data-analytics-in-2025--74883339Master SQL for Data Analytics in One Video!
This is the only SQL tutorial you need to become job-ready for Data Analytics, Data Science, and Business Intelligence roles.

In this full SQL course, we’ll go from absolute beginner to real-world advanced concepts with hands-on examples using a powerful products database.

Notes and code - https://github.com/AkarshVyas/SQL-Video-Content

What You’ll Learn:
SQL Basics – SELECT, WHERE, GROUP BY, ORDER BY
Filtering, Aggregations, and Advanced Clauses
Real-world SQL Projects & Test Scenarios
One-to-One, One-to-Many, and Many-to-Many Relationships
Views for Reporting & Optimization
Stored Procedures (PL/pgSQL) for Automation
Perfect for PostgreSQL, MySQL, and Interview Preparation


00:00:00 - 00:00:32 - intro
00:00:32 - 00:12:58 - SQL Basics
00:12:58 - 00:17:27 - Windows Installation
00:17:27 - 00:25:09 - MAC Installation
00:25:09 - 00:31:18 - Important things in PgAdmin
00:31:18 - 00:56:38 - Basic CRUD operations
00:56:38 - 01:16:27 - Data Types in SQL
01:16:27 - 01:29:54 - Constraints in SQL
01:29:54 - 01:46:00 - Exercise 1 / Test 1
01:46:00 - 01:54:13 - Some Problems
01:54:13 - 02:11:20 - Clauses in SQL
02:11:20 - 02:26:11 - Operators in SQL
02:26:11 - 02:32:02 - Aggregation Function
02:32:02 - 02:45:03 - Exercise 2 / Test 2
02:45:03 - 03:00:41 - String Functions
03:00:41 - 03:22:56 - Alter with Examples
03:22:56 - 03:42:24 - Case in SQL
03:42:24 - 03:48:11 - Relationships
03:48:11 - 03:59:37 - One to One Relationship
03:59:37 - 04:06:36 - One to Many relationship
04:06:36 - 04:19:33 - Joins
04:19:33 - 04:46:25 - Exercise 3 / Test 3
04:46:25 - 04:59:12 - Many to many Relationship
04:59:12 - 05:02:00 - Important Message
05:02:00 - 05:09:46 - Views is SQL
05:09:46 - 05:18:10 - Procedures
05:18:10 - 05:18:52 - Outro


Enjoy Love you all ❤️
#SQL #DataAnalytics #DataScience #SQLTutorial #LearnSQL #PostgreSQL #BI #PowerBI #SQLCourse #AnalyticsCareer #AkarshVyas]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677960Tue, 15 Jul 2025 14:30:43 +0000fertInstructor - Akarsh Vyas Master SQL for Data Analytics in One Video! This is the only SQL tutorial you need to become job-ready for Data Analytics, Data Science, and Business Intelligence roles. In this full SQL course, we’ll go from absolute...Master SQL for Data Analytics in One Video!
This is the only SQL tutorial you need to become job-ready for Data Analytics, Data Science, and Business Intelligence roles.

In this full SQL course, we’ll go from absolute beginner to real-world advanced concepts with hands-on examples using a powerful products database.

Notes and code - https://github.com/AkarshVyas/SQL-Video-Content

What You’ll Learn:
SQL Basics – SELECT, WHERE, GROUP BY, ORDER BY
Filtering, Aggregations, and Advanced Clauses
Real-world SQL Projects & Test Scenarios
One-to-One, One-to-Many, and Many-to-Many Relationships
Views for Reporting & Optimization
Stored Procedures (PL/pgSQL) for Automation
Perfect for PostgreSQL, MySQL, and Interview Preparation


00:00:00 - 00:00:32 - intro
00:00:32 - 00:12:58 - SQL Basics
00:12:58 - 00:17:27 - Windows Installation
00:17:27 - 00:25:09 - MAC Installation
00:25:09 - 00:31:18 - Important things in PgAdmin
00:31:18 - 00:56:38 - Basic CRUD operations
00:56:38 - 01:16:27 - Data Types in SQL
01:16:27 - 01:29:54 - Constraints in SQL
01:29:54 - 01:46:00 - Exercise 1 / Test 1
01:46:00 - 01:54:13 - Some Problems
01:54:13 - 02:11:20 - Clauses in SQL
02:11:20 - 02:26:11 - Operators in SQL
02:26:11 - 02:32:02 - Aggregation Function
02:32:02 - 02:45:03 - Exercise 2 / Test 2
02:45:03 - 03:00:41 - String Functions
03:00:41 - 03:22:56 - Alter with Examples
03:22:56 - 03:42:24 - Case in SQL
03:42:24 - 03:48:11 - Relationships
03:48:11 - 03:59:37 - One to One Relationship
03:59:37 - 04:06:36 - One to Many relationship
04:06:36 - 04:19:33 - Joins
04:19:33 - 04:46:25 - Exercise 3 / Test 3
04:46:25 - 04:59:12 - Many to many Relationship
04:59:12 - 05:02:00 - Important Message
05:02:00 - 05:09:46 - Views is SQL
05:09:46 - 05:18:10 - Procedures
05:18:10 - 05:18:52 - Outro


Enjoy Love you all ❤️
#SQL #DataAnalytics #DataScience #SQLTutorial #LearnSQL #PostgreSQL #BI #PowerBI #SQLCourse #AnalyticsCareer #AkarshVyas]]>19133falsefullhttps://www.spreaker.com/episode/complete-powerbi-course-for-data-analysis-and-visualization-job-oriented--74883345Master Power BI in Just 6 Hours!
Whether you're a complete beginner or looking to level up your data visualization skills, this full Power BI course is your all-in-one guide to become a Power BI pro for data analysis, dashboards, and business intelligence.

Perfect for: Students, professionals, data analysts, job seekers, business users

Covers everything from A to Z:
– Power BI basics and interface
– Connecting to various data sources
– Data transformation with Power Query
– Creating interactive reports and dashboards
– DAX formulas and calculations
– Data modeling and relationships
– Publishing and sharing reports

📂 All the File Links – https://github.com/master-dhanesh/YT-Power-BI-Practice-Sheet

Power BI is one of the most powerful and in-demand tools in the world of business intelligence. Used by companies across industries like finance, marketing, sales, HR, and analytics — mastering Power BI gives you a huge edge in the job market.

This course is designed to make learning fast, practical, and impactful — no matter your background.

Like, Share & Subscribe for full courses on Power BI, Excel, Python, AI, Data Science & more!]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677991Mon, 07 Jul 2025 14:30:20 +0000fertInstructor in this video – Dhanesh Malviya Master Power BI in Just 6 Hours! Whether you're a complete beginner or looking to level up your data visualization skills, this full Power BI course is your all-in-one guide to become a Power BI pro for data...Master Power BI in Just 6 Hours!
Whether you're a complete beginner or looking to level up your data visualization skills, this full Power BI course is your all-in-one guide to become a Power BI pro for data analysis, dashboards, and business intelligence.

Perfect for: Students, professionals, data analysts, job seekers, business users

Covers everything from A to Z:
– Power BI basics and interface
– Connecting to various data sources
– Data transformation with Power Query
– Creating interactive reports and dashboards
– DAX formulas and calculations
– Data modeling and relationships
– Publishing and sharing reports

📂 All the File Links – https://github.com/master-dhanesh/YT-Power-BI-Practice-Sheet

Power BI is one of the most powerful and in-demand tools in the world of business intelligence. Used by companies across industries like finance, marketing, sales, HR, and analytics — mastering Power BI gives you a huge edge in the job market.

This course is designed to make learning fast, practical, and impactful — no matter your background.

Like, Share & Subscribe for full courses on Power BI, Excel, Python, AI, Data Science & more!]]>18991falsefullhttps://www.spreaker.com/episode/10k-milestone-reached-qna-session-what-s-coming-next--74883323In this LIVE session, I’ll be sharing what’s next for the channel, upcoming content plans, new series announcements, and how YOU can be a part of it all. From AI & Machine Learning to Real-world Projects, we’re going big.

💬 Come join the celebration, ask your questions, and let’s build the future together!
If you've been learning with me — this is your moment to shape what comes next.
Thank you for being here. Let’s aim for 100K now! 💯]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677984Thu, 03 Jul 2025 15:39:14 +0000fertWe've officially hit 10,000 subscribers — and this is just the beginning! 🙌 In this LIVE session, I’ll be sharing what’s next for the channel, upcoming content plans, new series announcements, and how YOU can be a part of it all. From AI & Machine...In this LIVE session, I’ll be sharing what’s next for the channel, upcoming content plans, new series announcements, and how YOU can be a part of it all. From AI & Machine Learning to Real-world Projects, we’re going big.

💬 Come join the celebration, ask your questions, and let’s build the future together!
If you've been learning with me — this is your moment to shape what comes next.
Thank you for being here. Let’s aim for 100K now! 💯]]>2766falsefullhttps://www.spreaker.com/episode/complete-ms-excel-course-for-data-analyst-job-oriented--74883336Master Microsoft Excel in Just 6 Hours!
Whether you're a complete beginner or someone looking to sharpen your Excel skills, this full course is your all-in-one guide to become a pro in Excel for data analysis, reporting, and productivity

Perfect for: Students, professionals, data analysts, job seekers, business users
Covers everything from A to Z:
– Excel basics and interface
– Formulas, functions (SUM, IF, VLOOKUP, INDEX-MATCH, etc.)
– Data analysis techniques
– Pivot Tables and Pivot Charts
– Conditional Formatting
– Charts and visualizations

All the File Links - https://github.com/master-dhanesh/YT-Ms-Excel-Practice-Sheet

📈 Excel is one of the most in-demand tools across industries like finance, marketing, HR, data science, and management. Learning Excel the right way can boost your productivity, unlock new job opportunities, and make you a power user in your team.

No matter your background, this course is structured to help you learn fast and effectively.

Like, Share & Subscribe for full courses on Excel, Python, AI, Data Science & more!

00:00:00 - 00:01:55 - Introduction
00:01:55 - 01:04:03 - Basics of MS Excel
01:04:03 - 02:38:53 - Excel based Wrangling
02:38:53 - 03:10:31 - Power query based Wrangling
03:10:31 - 04:31:01 - Data modelling and DAX with Power Pivot
04:31:01 - 05:55:26 - Analysis and Visualization with Pivot Tables
05:55:26 - 05:55:55 - Outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677981Tue, 01 Jul 2025 14:30:31 +0000fertInstructor in this video - Dhanesh Malviya Master Microsoft Excel in Just 6 Hours! Whether you're a complete beginner or someone looking to sharpen your Excel skills, this full course is your all-in-one guide to become a pro in Excel for data...Master Microsoft Excel in Just 6 Hours!
Whether you're a complete beginner or someone looking to sharpen your Excel skills, this full course is your all-in-one guide to become a pro in Excel for data analysis, reporting, and productivity

Perfect for: Students, professionals, data analysts, job seekers, business users
Covers everything from A to Z:
– Excel basics and interface
– Formulas, functions (SUM, IF, VLOOKUP, INDEX-MATCH, etc.)
– Data analysis techniques
– Pivot Tables and Pivot Charts
– Conditional Formatting
– Charts and visualizations

All the File Links - https://github.com/master-dhanesh/YT-Ms-Excel-Practice-Sheet

📈 Excel is one of the most in-demand tools across industries like finance, marketing, HR, data science, and management. Learning Excel the right way can boost your productivity, unlock new job opportunities, and make you a power user in your team.

No matter your background, this course is structured to help you learn fast and effectively.

Like, Share & Subscribe for full courses on Excel, Python, AI, Data Science & more!

00:00:00 - 00:01:55 - Introduction
00:01:55 - 01:04:03 - Basics of MS Excel
01:04:03 - 02:38:53 - Excel based Wrangling
02:38:53 - 03:10:31 - Power query based Wrangling
03:10:31 - 04:31:01 - Data modelling and DAX with Power Pivot
04:31:01 - 05:55:26 - Analysis and Visualization with Pivot Tables
05:55:26 - 05:55:55 - Outro]]>21356falsefullhttps://www.spreaker.com/episode/part-4-model-tuning-ensemble-unsupervised-learning-full-ml-course-sheryians-ai-school--74883329Welcome to Part 4 of our Complete Machine Learning Series!
In this session, we take your ML skills to the next level — learning how to improve model performance, explore unsupervised learning, and build even stronger models with advanced techniques.

What you’ll learn:
– What is Model Tuning and why it matters
– Cross-Validation: Testing models the right way
– Hyperparameter Tuning: Grid Search CV, Randomized Search CV
– Ensemble Learning: Bagging, Boosting, Stacking explained
– Random Forest Classifier: Powerful tree-based model
– AdaBoost, Gradient Boosting, XGBoost: Taking boosting to the next level
– What is Unsupervised Learning
– Clustering Algorithms:
 – K-Means Clustering + Elbow Method
 – DBSCAN: Clustering any shape + outliers
– Dimensionality Reduction:
 – PCA (Principal Component Analysis)
 – Curse of Dimensionality — why it matters
– Hands-on Projects:
 – K-Means Clustering on real data
 – DBSCAN project — complex clusters
 – PCA visualizations

By the end of this video, you'll have a solid grasp of advanced ML techniques — and you'll be ready to tackle real-world data science problems with confidence.

Links:
📝 Suggestion — Create your own structured notes during the video📚 My notes 🥲 — https://drive.google.com/file/d/1Xf6760AzL2hr1PKYC4VFRI0eNU6DTumZ/view?usp=sharing
Code link - https://github.com/AkarshVyas/Machine_learning_part4


📌 Don’t forget to check out Part 1, Part 2 & Part 3 if you haven’t already — this is a complete series!👍 Like, share, and subscribe for more ML tutorials & hands-on projects!

00:00:00 - 00:00:55 intro
00:01:25 - 00:03:29 contents of the video
00:03:29 - 00:10:46 model tuning
00:10:46 - 00:19:02 cross validation
00:19:02 - 00:27:12 code implementation or cross validation
00:27:12 - 00:33:26 hyperparameter tuning
00:33:26 - 00:43:15 grid search cv
00:43:15 - 01:05:12 code implementation of grid search cv
01:05:12 - 01:09:49 random search cv
01:09:49 - 01:14:09 random search cv implementation
01:14:09 - 01:22:56 ensemble learning
01:22:56 - 01:27:56 stacking
01:27:56 - 01:32:00 bagging
01:32:00 - 01:34:14 boosting
01:34:14 - 01:49:54 code implementation of stacking
01:49:54 - 02:07:46 implementation of bagging
02:07:46 - 02:17:12 implementation of boosting
02:17:12 - 02:33:00 adaboost, gradient boost, xgboost
02:33:00 - 02:45:31 unsupervised learning
02:45:31 - 03:05:38 K-means clustering algorithm
03:05:38 - 03:14:27 K-means implementation
03:18:29 - 03:24:27 DB scan algorithm
03:24:27 - 03:29:53 implementation of dbscan
03:29:53 - 03:49:45 dimensionality reduction
03:49:45 - 03:55:02 implementation of PCA for dimensionality reduction
03:55:02 - 03:59:16 some final words
03:59:16 - 04:00:09 outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678016Mon, 23 Jun 2025 14:30:23 +0000fertInstructor - Akarsh Vyas Welcome to Part 4 of our Complete Machine Learning Series! In this session, we take your ML skills to the next level — learning how to improve model performance, explore unsupervised learning, and build even stronger models...Welcome to Part 4 of our Complete Machine Learning Series!
In this session, we take your ML skills to the next level — learning how to improve model performance, explore unsupervised learning, and build even stronger models with advanced techniques.

What you’ll learn:
– What is Model Tuning and why it matters
– Cross-Validation: Testing models the right way
– Hyperparameter Tuning: Grid Search CV, Randomized Search CV
– Ensemble Learning: Bagging, Boosting, Stacking explained
– Random Forest Classifier: Powerful tree-based model
– AdaBoost, Gradient Boosting, XGBoost: Taking boosting to the next level
– What is Unsupervised Learning
– Clustering Algorithms:
 – K-Means Clustering + Elbow Method
 – DBSCAN: Clustering any shape + outliers
– Dimensionality Reduction:
 – PCA (Principal Component Analysis)
 – Curse of Dimensionality — why it matters
– Hands-on Projects:
 – K-Means Clustering on real data
 – DBSCAN project — complex clusters
 – PCA visualizations

By the end of this video, you'll have a solid grasp of advanced ML techniques — and you'll be ready to tackle real-world data science problems with confidence.

Links:
📝 Suggestion — Create your own structured notes during the video📚 My notes 🥲 — https://drive.google.com/file/d/1Xf6760AzL2hr1PKYC4VFRI0eNU6DTumZ/view?usp=sharing
Code link - https://github.com/AkarshVyas/Machine_learning_part4


📌 Don’t forget to check out Part 1, Part 2 & Part 3 if you haven’t already — this is a complete series!👍 Like, share, and subscribe for more ML tutorials & hands-on projects!

00:00:00 - 00:00:55 intro
00:01:25 - 00:03:29 contents of the video
00:03:29 - 00:10:46 model tuning
00:10:46 - 00:19:02 cross validation
00:19:02 - 00:27:12 code implementation or cross validation
00:27:12 - 00:33:26 hyperparameter tuning
00:33:26 - 00:43:15 grid search cv
00:43:15 - 01:05:12 code implementation of grid search cv
01:05:12 - 01:09:49 random search cv
01:09:49 - 01:14:09 random search cv implementation
01:14:09 - 01:22:56 ensemble learning
01:22:56 - 01:27:56 stacking
01:27:56 - 01:32:00 bagging
01:32:00 - 01:34:14 boosting
01:34:14 - 01:49:54 code implementation of stacking
01:49:54 - 02:07:46 implementation of bagging
02:07:46 - 02:17:12 implementation of boosting
02:17:12 - 02:33:00 adaboost, gradient boost, xgboost
02:33:00 - 02:45:31 unsupervised learning
02:45:31 - 03:05:38 K-means clustering algorithm
03:05:38 - 03:14:27 K-means implementation
03:18:29 - 03:24:27 DB scan algorithm
03:24:27 - 03:29:53 implementation of dbscan
03:29:53 - 03:49:45 dimensionality reduction
03:49:45 - 03:55:02 implementation of PCA for dimensionality reduction
03:55:02 - 03:59:16 some final words
03:59:16 - 04:00:09 outro]]>14410falsefullhttps://www.spreaker.com/episode/part-3-supervised-learning-classification-algorithms-for-beginners-sheryians-ai-school--74883335Welcome to Part 3 of our complete Machine Learning series. In this session, we dive into the world of Supervised Learning – Classification Models. From understanding what classification is to implementing multiple powerful algorithms, this video is packed with both theory and practical knowledge to help you build real-world classifiers.

What you’ll learn:
– What is Classification and where it’s used
– Logistic Regression: The go-to for binary classification
– K-Nearest Neighbors (KNN): Classifying by similarity
– Decision Trees: Learning decisions step by step
– Naive Bayes: Probabilistic and surprisingly powerful
– Support Vector Machine (SVM): Drawing the best boundary
– Evaluation Metrics to test your model:
– Accuracy, Precision, Recall, F1-score
– Confusion Matrix – reading and interpreting results
– Hands-on Project: Titanic Survival Classification using real data

Whether you're a beginner trying to understand classification or a student aiming to master multiple algorithms, this video blends concepts + code + clarity for maximum learning.

Links:
📝 Suggestion – Create your own structured notes during the video
📚 My notes 🥲 – https://drive.google.com/file/d/1pQZ1Zga_u4z2L1ogLxU41Y_7LI1TLaPY/view?usp=sharing

Titanic project
Colab Notebook: https://colab.research.google.com/drive/1iIujBR7WcySa15Z3JLdVRKcHT7YO-q9X?usp=sharing

Final project Github link - https://github.com/AkarshVyas/Machine-Learning-Part-3

📌 Don’t forget to check out Part 1 & Part 2 if you haven’t already.
👍 Like, share, and subscribe for more upcoming ML tutorials & hands-on projects!

00:00:00 - 00:01:07 Introduction
00:01:07 - 00:01:28 Important note
00:01:28 - 00:05:11 Structure of Video
00:05:11 - 00:08:32 What is Classification
00:08:32 - 00:27:27 Logistic Regression
00:27:27 - 00:31:21 Linear regression vs Logistic regression
00:31:21 - 00:45:11 Log Loss function
00:45:11 - 00:56:24 Logistic Regression Implementation
00:56:24 - 01:16:22 Model Evaluation
01:16:22 - 01:20:17 Model Evaluation Implementation
01:20:17 - 01:34:04 KNN
01:34:04 - 01:42:32 KNN Implementation
01:42:32 - 01:58:50 naive bayes
01:58:50 - 02:05:38 Naive bayes Implementation
02:05:38 - 02:34:36 Decision Trees
02:34:36 - 02:42:41 Decision Tree implementation
02:42:41 - 02:55:56 Basics of SVM
02:55:56 - 03:02:15 application of SVM
03:02:15 - 03:21:22 final project
03:21:22 - 03:39:04 frontend
03:39:04 - 03:39:37 outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677971Tue, 17 Jun 2025 14:01:26 +0000fertInstructor - Akarsh Vyas Welcome to Part 3 of our complete Machine Learning series. In this session, we dive into the world of Supervised Learning – Classification Models. From understanding what classification is to implementing multiple powerful...Welcome to Part 3 of our complete Machine Learning series. In this session, we dive into the world of Supervised Learning – Classification Models. From understanding what classification is to implementing multiple powerful algorithms, this video is packed with both theory and practical knowledge to help you build real-world classifiers.

What you’ll learn:
– What is Classification and where it’s used
– Logistic Regression: The go-to for binary classification
– K-Nearest Neighbors (KNN): Classifying by similarity
– Decision Trees: Learning decisions step by step
– Naive Bayes: Probabilistic and surprisingly powerful
– Support Vector Machine (SVM): Drawing the best boundary
– Evaluation Metrics to test your model:
– Accuracy, Precision, Recall, F1-score
– Confusion Matrix – reading and interpreting results
– Hands-on Project: Titanic Survival Classification using real data

Whether you're a beginner trying to understand classification or a student aiming to master multiple algorithms, this video blends concepts + code + clarity for maximum learning.

Links:
📝 Suggestion – Create your own structured notes during the video
📚 My notes 🥲 – https://drive.google.com/file/d/1pQZ1Zga_u4z2L1ogLxU41Y_7LI1TLaPY/view?usp=sharing

Titanic project
Colab Notebook: https://colab.research.google.com/drive/1iIujBR7WcySa15Z3JLdVRKcHT7YO-q9X?usp=sharing

Final project Github link - https://github.com/AkarshVyas/Machine-Learning-Part-3

📌 Don’t forget to check out Part 1 & Part 2 if you haven’t already.
👍 Like, share, and subscribe for more upcoming ML tutorials & hands-on projects!

00:00:00 - 00:01:07 Introduction
00:01:07 - 00:01:28 Important note
00:01:28 - 00:05:11 Structure of Video
00:05:11 - 00:08:32 What is Classification
00:08:32 - 00:27:27 Logistic Regression
00:27:27 - 00:31:21 Linear regression vs Logistic regression
00:31:21 - 00:45:11 Log Loss function
00:45:11 - 00:56:24 Logistic Regression Implementation
00:56:24 - 01:16:22 Model Evaluation
01:16:22 - 01:20:17 Model Evaluation Implementation
01:20:17 - 01:34:04 KNN
01:34:04 - 01:42:32 KNN Implementation
01:42:32 - 01:58:50 naive bayes
01:58:50 - 02:05:38 Naive bayes Implementation
02:05:38 - 02:34:36 Decision Trees
02:34:36 - 02:42:41 Decision Tree implementation
02:42:41 - 02:55:56 Basics of SVM
02:55:56 - 03:02:15 application of SVM
03:02:15 - 03:21:22 final project
03:21:22 - 03:39:04 frontend
03:39:04 - 03:39:37 outro]]>13178falsefullhttps://www.spreaker.com/episode/part-2-supervised-learning-complete-machine-learning-course-for-beginners-sheryians-ai-school--74883337Welcome to Part 2 of our complete Machine Learning series. In this session, we dive deep into Supervised Learning, focusing on Regression Models – especially Linear Regression. This video is packed with theory, intuition, and hands-on implementation to help you build real predictive models.
What you’ll learn:
* What is Regression and where it's used
* Linear Regression: Concept and Intuition
* Light introduction to Cost Function and Gradient Descent
* How to use Scikit-learn to implement Linear Regression
* Model Evaluation Metrics: MSE, RMSE, R² Score
* Train-Test Split: Why it matters
* Understanding Overfitting and Underfitting with visuals
* Hands-on Project: Predict House Prices using Linear Regression
Whether you're a beginner exploring machine learning or a student brushing up your concepts, this video is designed to give you clarity, practical knowledge, and confidence to move ahead.
Links:
Suggestion - create your own structured notes.
My notes 🥲 - https://drive.google.com/file/d/1K2uvS3IVpq6RTEqETPybTck-tLtXKQws/view?usp=sharing
* Kaggle Notebook: https://www.kaggle.com/code/akarshvyas/notebook9fdd2dc0b8
* Collab notebook : https://colab.research.google.com/drive/1QlZkG9BSj_JHeqcjidEuVj-gTmwxLvBi?usp=sharing

Don't forget to check out Part 1 if you haven’t already.Like, share, and subscribe for more upcoming machine learning tutorials.

00:00:00 - 00:01:27 intro
00:01:27 - 00:01:31 important note
00:01:31 - 00:02:58 intro 2
00:02:58 - 00:06:29 contents of the video
00:06:29 - 00:12:04 what is regression
00:12:04 - 00:38:47 linear regression
00:38:47 - 00:46:30 cost function
00:46:30 - 01:04:26 gradient descent
01:04:26 - 01:10:59 repeat convergence theorem
01:10:59 - 01:14:56 hyperplane
01:14:56 - 01:28:46 project
01:28:46 - 01:46:17 y_test
01:46:17 - 01:57:37 overfitting and underfitting
01:57:37 - 02:40:45 project 2
02:40:45 - 02:41:17 outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678003Tue, 10 Jun 2025 14:30:14 +0000fertInstructor - Akarsh Vyas Welcome to Part 2 of our complete Machine Learning series. In this session, we dive deep into Supervised Learning, focusing on Regression Models – especially Linear Regression. This video is packed with theory, intuition, and...Welcome to Part 2 of our complete Machine Learning series. In this session, we dive deep into Supervised Learning, focusing on Regression Models – especially Linear Regression. This video is packed with theory, intuition, and hands-on implementation to help you build real predictive models.
What you’ll learn:
* What is Regression and where it's used
* Linear Regression: Concept and Intuition
* Light introduction to Cost Function and Gradient Descent
* How to use Scikit-learn to implement Linear Regression
* Model Evaluation Metrics: MSE, RMSE, R² Score
* Train-Test Split: Why it matters
* Understanding Overfitting and Underfitting with visuals
* Hands-on Project: Predict House Prices using Linear Regression
Whether you're a beginner exploring machine learning or a student brushing up your concepts, this video is designed to give you clarity, practical knowledge, and confidence to move ahead.
Links:
Suggestion - create your own structured notes.
My notes 🥲 - https://drive.google.com/file/d/1K2uvS3IVpq6RTEqETPybTck-tLtXKQws/view?usp=sharing
* Kaggle Notebook: https://www.kaggle.com/code/akarshvyas/notebook9fdd2dc0b8
* Collab notebook : https://colab.research.google.com/drive/1QlZkG9BSj_JHeqcjidEuVj-gTmwxLvBi?usp=sharing

Don't forget to check out Part 1 if you haven’t already.Like, share, and subscribe for more upcoming machine learning tutorials.

00:00:00 - 00:01:27 intro
00:01:27 - 00:01:31 important note
00:01:31 - 00:02:58 intro 2
00:02:58 - 00:06:29 contents of the video
00:06:29 - 00:12:04 what is regression
00:12:04 - 00:38:47 linear regression
00:38:47 - 00:46:30 cost function
00:46:30 - 01:04:26 gradient descent
01:04:26 - 01:10:59 repeat convergence theorem
01:10:59 - 01:14:56 hyperplane
01:14:56 - 01:28:46 project
01:28:46 - 01:46:17 y_test
01:46:17 - 01:57:37 overfitting and underfitting
01:57:37 - 02:40:45 project 2
02:40:45 - 02:41:17 outro]]>9678falsefullhttps://www.spreaker.com/episode/complete-machine-learning-course-for-beginners-part-1-foundation-sheryians-ai-school--74883342Welcome to the first step of your Machine Learning journey!
In this video, we’ll walk through the complete foundation of a real-world ML project, covering everything you must know before building any model.

you can download the CSV files and code from here.
Code link - https://github.com/AkarshVyas/Machine-Learning-Part-1

All the notes of our classes are here
Notes - https://drive.google.com/file/d/16GDJ6Ut9IX0RNYDnGUynbrjeftfjnB59/view?usp=sharing

Here's what you'll learn:

How to define the problem clearly

Where and how to collect quality data

How to perform Exploratory Data Analysis (EDA)

Techniques for data cleaning and preprocessing

Feature selection to choose the right data

Feature engineering to boost model performance

These are the most critical and often ignored steps in ML — but they make or break your model’s success. Whether you're a beginner or refreshing your knowledge, this video sets the stage for smarter models and real-world success.

Start here. Build right.

00:00 - 00:35 - Introduction
00:35 - 02:54 - Content
02:54 - 06:52 - what is machine learning
06:52 - 08:47 - Real life machine learning applications
08:47 - 10:22 - Traditional programming vs machine learning
10:22 - 14:34 - Difference b/w AI,ML,DL
14:34 - 25:20 - Types of Machine Learning
25:20 - 28:15 - Steps for making a machine learning model
28:15 - 33:45 - EDA
33:45 - 42:30 - DATA cleaning
42:30 - 54:10- DATA Preprocessing
54:10 - 57:58 - Feature Engineering
57:58 - 01:01:42 - Feature Selection
01:01:42 - 02:07:15 - Project 1
02:07:15 - 02:42:43- Project 2
02:42:43 - 02:43:07 -outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678029Mon, 02 Jun 2025 14:29:56 +0000fertInstructor - Akarsh Vyas Welcome to the first step of your Machine Learning journey! In this video, we’ll walk through the complete foundation of a real-world ML project, covering everything you must know before building any model. you can download...Welcome to the first step of your Machine Learning journey!
In this video, we’ll walk through the complete foundation of a real-world ML project, covering everything you must know before building any model.

you can download the CSV files and code from here.
Code link - https://github.com/AkarshVyas/Machine-Learning-Part-1

All the notes of our classes are here
Notes - https://drive.google.com/file/d/16GDJ6Ut9IX0RNYDnGUynbrjeftfjnB59/view?usp=sharing

Here's what you'll learn:

How to define the problem clearly

Where and how to collect quality data

How to perform Exploratory Data Analysis (EDA)

Techniques for data cleaning and preprocessing

Feature selection to choose the right data

Feature engineering to boost model performance

These are the most critical and often ignored steps in ML — but they make or break your model’s success. Whether you're a beginner or refreshing your knowledge, this video sets the stage for smarter models and real-world success.

Start here. Build right.

00:00 - 00:35 - Introduction
00:35 - 02:54 - Content
02:54 - 06:52 - what is machine learning
06:52 - 08:47 - Real life machine learning applications
08:47 - 10:22 - Traditional programming vs machine learning
10:22 - 14:34 - Difference b/w AI,ML,DL
14:34 - 25:20 - Types of Machine Learning
25:20 - 28:15 - Steps for making a machine learning model
28:15 - 33:45 - EDA
33:45 - 42:30 - DATA cleaning
42:30 - 54:10- DATA Preprocessing
54:10 - 57:58 - Feature Engineering
57:58 - 01:01:42 - Feature Selection
01:01:42 - 02:07:15 - Project 1
02:07:15 - 02:42:43- Project 2
02:42:43 - 02:43:07 -outro]]>9788falsefullhttps://www.spreaker.com/episode/complete-statistics-course-for-beginners-data-science-tutorial-sheryians-ai-school--74883407Complete Statistics for Data Science in One Video (5 Hours!)
Master the most important statistics concepts required for Data Science, Machine Learning, and AI — all in one detailed, beginner-friendly crash course.

In this video, we cover everything from descriptive statistics, probability, inferential statistics, to hypothesis testing, distributions, confidence intervals, correlation & regression, and more — explained with examples, visuals, and real-world data science context.

GitHub link - https://github.com/AkarshVyas/youtube-Statistics
Notes - https://drive.google.com/file/d/1MZoDojzmUtYz8GI9aeih-tCThCDKXwp0/view?usp=sharing

✅ Topics Covered:

What is Statistics?

Types of Data & Scales of Measurement

Measures of Central Tendency (Mean, Median, Mode)

Measures of Dispersion (Range, Variance, Standard Deviation, IQR)

Probability & Conditional Probability

Bayes' Theorem

Probability Distributions (Normal, Binomial, Poisson)

Hypothesis Testing (Z-test, T-test, Chi-square test, ANOVA)

Confidence Intervals

Correlation vs Causation

p-value and Statistical Significance

Statistical Thinking for Machine Learning
...and much more!

Whether you're a Data Science student, ML enthusiast, or preparing for interviews, this video has everything you need to understand statistics deeply.

No prior experience needed — ideal for absolute beginners!

Don't forget to like, comment, and subscribe for more in-depth tutorials on Data Science and AI.

00:00 - 00:25 - Introduction
00:25 - 34:02 - Statistical Visualization
34:02 - 43:18 - Measure of Central Tendency
43:18 - 54:13 - Measure of Spread
54:13 - 01:01:29 - Outliers
01:01:29 - 01:06:59 - 5 number summary
01:06:59 - 01:14:15 - Outliers Code
01:14:15 - 01:26:00 - Variance and Standard Deviation
01:26:00 - 01:38:09 - Density Curve
01:38:09 - 01:54:44 - Z score
01:54:44 - 02:01:15 - Basic Probablity
02:01:15 - 02:09:59 - Probablity Events
02:09:59 - 02:20:55 - Addition Rule and Multiplication Rule
02:20:55 - 02:38:19 - Conditional Probablity
02:38:19 - 02:48:03 - Bayes Theorem
02:48:03 - 03:08:04 - Hypothesis testing Basics
03:08:04 - 03:31:35 - Z-test
03:31:35 - 03:40:53 - Z-Test Code Implementation
03:40:53 - 03:50:52 - T-Test
03:50:52 - 03:58:04 - T-Test Code Implementation
03:58:04 - 04:09:34 - Two Sample Test
04:09:34 - 04:14:57 - Two Sample Test Code
04:14:57 - 04:29:19 - Chi Square Test
04:29:19 - 04:38:07 - Chi Square Test Code
04:38:07 - 04:48:05 - Annova Test
04:48:05 - 04:55:42 - Covariance and Correlation
04:55:42 - 04:56:00 - Outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678034Tue, 20 May 2025 14:30:35 +0000fertInstructor in this video - Akarsh Vyas Complete Statistics for Data Science in One Video (5 Hours!) Master the most important statistics concepts required for Data Science, Machine Learning, and AI — all in one detailed, beginner-friendly crash...Complete Statistics for Data Science in One Video (5 Hours!)
Master the most important statistics concepts required for Data Science, Machine Learning, and AI — all in one detailed, beginner-friendly crash course.

In this video, we cover everything from descriptive statistics, probability, inferential statistics, to hypothesis testing, distributions, confidence intervals, correlation & regression, and more — explained with examples, visuals, and real-world data science context.

GitHub link - https://github.com/AkarshVyas/youtube-Statistics
Notes - https://drive.google.com/file/d/1MZoDojzmUtYz8GI9aeih-tCThCDKXwp0/view?usp=sharing

✅ Topics Covered:

What is Statistics?

Types of Data & Scales of Measurement

Measures of Central Tendency (Mean, Median, Mode)

Measures of Dispersion (Range, Variance, Standard Deviation, IQR)

Probability & Conditional Probability

Bayes' Theorem

Probability Distributions (Normal, Binomial, Poisson)

Hypothesis Testing (Z-test, T-test, Chi-square test, ANOVA)

Confidence Intervals

Correlation vs Causation

p-value and Statistical Significance

Statistical Thinking for Machine Learning
...and much more!

Whether you're a Data Science student, ML enthusiast, or preparing for interviews, this video has everything you need to understand statistics deeply.

No prior experience needed — ideal for absolute beginners!

Don't forget to like, comment, and subscribe for more in-depth tutorials on Data Science and AI.

00:00 - 00:25 - Introduction
00:25 - 34:02 - Statistical Visualization
34:02 - 43:18 - Measure of Central Tendency
43:18 - 54:13 - Measure of Spread
54:13 - 01:01:29 - Outliers
01:01:29 - 01:06:59 - 5 number summary
01:06:59 - 01:14:15 - Outliers Code
01:14:15 - 01:26:00 - Variance and Standard Deviation
01:26:00 - 01:38:09 - Density Curve
01:38:09 - 01:54:44 - Z score
01:54:44 - 02:01:15 - Basic Probablity
02:01:15 - 02:09:59 - Probablity Events
02:09:59 - 02:20:55 - Addition Rule and Multiplication Rule
02:20:55 - 02:38:19 - Conditional Probablity
02:38:19 - 02:48:03 - Bayes Theorem
02:48:03 - 03:08:04 - Hypothesis testing Basics
03:08:04 - 03:31:35 - Z-test
03:31:35 - 03:40:53 - Z-Test Code Implementation
03:40:53 - 03:50:52 - T-Test
03:50:52 - 03:58:04 - T-Test Code Implementation
03:58:04 - 04:09:34 - Two Sample Test
04:09:34 - 04:14:57 - Two Sample Test Code
04:14:57 - 04:29:19 - Chi Square Test
04:29:19 - 04:38:07 - Chi Square Test Code
04:38:07 - 04:48:05 - Annova Test
04:48:05 - 04:55:42 - Covariance and Correlation
04:55:42 - 04:56:00 - Outro]]>17762falsefullhttps://www.spreaker.com/episode/complete-data-visualization-course-for-beginners-matplotlib-seaborn-sheryians-ai-school--74883338
Instructor – Akarsh Vyas

✅ What You’ll Learn:
* Why Data Visualization is a must-have skill in Data Science
* Basics of Matplotlib – your first step into visual magic
* Stylish plots and insights using Seaborn
* Interactive graphs using Plotly
* Real-world mini project to tie it all together
* And lots of tips, tricks & shortcuts to impress your data team! 💡

🎯 This is not just theory – it’s practical, visual, and hands-on. Perfect for anyone into Data Science, ML, AI, or Analytics. Let’s turn your data into stories! 📈✨
🔥 Source Code & Project Files – https://github.com/AkarshVyas/Data-Visualization-Youtube
📌 Don’t forget to like, comment, and subscribe to Sheryians AI School for more exciting and beginner-friendly data science content!


00:00 - 00:20 - Introduction
00:20 - 02:49 - Origin story
02:49 - 05:29 - Types of Data visualization
05:29 - 41:21 - Matplotlib
41:21 - 01:05:57 - Distribution plots
01:05:57 - 01:23:36 - categorical plots
01:23:36 - 01:37:09 - Matrix plots
01:37:09 - 01:45:09 - Regression plots
01:45:09 - 01:55:53 - Plotly and Cufflinks
01:55:53 - 02:34:44 - IPL project
02:34:44 - 02:35:07 - Outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678002Mon, 12 May 2025 14:31:04 +0000fertWelcome to the Complete Data Visualization in Python Course! 📊🔥In this full video tutorial, we’re diving deep into the world of Data Visualization using Matplotlib, Seaborn, and Plotly — with real projects and practical use-cases. Whether you're a...
Instructor – Akarsh Vyas

✅ What You’ll Learn:
* Why Data Visualization is a must-have skill in Data Science
* Basics of Matplotlib – your first step into visual magic
* Stylish plots and insights using Seaborn
* Interactive graphs using Plotly
* Real-world mini project to tie it all together
* And lots of tips, tricks & shortcuts to impress your data team! 💡

🎯 This is not just theory – it’s practical, visual, and hands-on. Perfect for anyone into Data Science, ML, AI, or Analytics. Let’s turn your data into stories! 📈✨
🔥 Source Code & Project Files – https://github.com/AkarshVyas/Data-Visualization-Youtube
📌 Don’t forget to like, comment, and subscribe to Sheryians AI School for more exciting and beginner-friendly data science content!


00:00 - 00:20 - Introduction
00:20 - 02:49 - Origin story
02:49 - 05:29 - Types of Data visualization
05:29 - 41:21 - Matplotlib
41:21 - 01:05:57 - Distribution plots
01:05:57 - 01:23:36 - categorical plots
01:23:36 - 01:37:09 - Matrix plots
01:37:09 - 01:45:09 - Regression plots
01:45:09 - 01:55:53 - Plotly and Cufflinks
01:55:53 - 02:34:44 - IPL project
02:34:44 - 02:35:07 - Outro]]>9308falsefullhttps://www.spreaker.com/episode/complete-data-science-course-for-beginners-pandas-library-sheryians-ai-school--74883340Welcome to the Complete Pandas Course!
In this 2.5-hour full tutorial, we’ll take you from absolute beginner to mastering Pandas — the go-to library for Data Analysis and Data Manipulation in Python.

What you’ll learn in this course:
✅ Introduction to Pandas and why it’s essential for data analysis
✅ Series and DataFrames explained in simple terms
✅ Data cleaning: handling missing values, duplicates
✅ Filtering, sorting, and selecting data
✅ Data aggregation and groupby operations
✅ Merging, joining, and concatenating datasets
✅ Real-world mini projects to apply Pandas skills
✅ And much more to make you ready for data-driven roles!

🔥 Source Code & Notebooks – https://github.com/AkarshVyas/Pandas-Youtube

Whether you’re diving into Data Science, Machine Learning, or Data Analytics, this video will equip you with practical Pandas skills that professionals use every day. 🚀

📌 Don’t forget to like, share, and subscribe for more full courses on Data Science, AI, Machine Learning, and beyond!

#PandasCourse #LearnPandas #PandasTutorial #PythonDataAnalysis #SheryiansAISchool #PythonForDataScience #FreePandasCourse #sheryianscodingschool

00:00 - 00:25 - Intro
00:25 - 02:24 - Origin story of Pandas
02:24 - 03:32 - Table of content
03:32 - 11:27 - Pandas Series
11:27 - 35:20 - Dataframes in Pandas
35:20 - 45:33 - Missing Data
45:33 - 57:46 - Merging Joining and concatination
57:46 - 01:08:02 - GroupBy and Aggregation
01:08:02 - 01:17:20 - Pivot Tables
01:17:20 - 01:24:47 - Operations
01:24:47 - 01:27:58 - Finding Data
01:27:58 - 01:56:19 - Feature Extraction Project
01:56:19 - 02:23:16 - Data Capstone Project
02:23:16 - 02:23:37 - Outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677968Mon, 05 May 2025 14:30:28 +0000fertInstructor in this video – Akarsh Vyas Welcome to the Complete Pandas Course! In this 2.5-hour full tutorial, we’ll take you from absolute beginner to mastering Pandas — the go-to library for Data Analysis and Data Manipulation in Python. What you’ll...Welcome to the Complete Pandas Course!
In this 2.5-hour full tutorial, we’ll take you from absolute beginner to mastering Pandas — the go-to library for Data Analysis and Data Manipulation in Python.

What you’ll learn in this course:
✅ Introduction to Pandas and why it’s essential for data analysis
✅ Series and DataFrames explained in simple terms
✅ Data cleaning: handling missing values, duplicates
✅ Filtering, sorting, and selecting data
✅ Data aggregation and groupby operations
✅ Merging, joining, and concatenating datasets
✅ Real-world mini projects to apply Pandas skills
✅ And much more to make you ready for data-driven roles!

🔥 Source Code & Notebooks – https://github.com/AkarshVyas/Pandas-Youtube

Whether you’re diving into Data Science, Machine Learning, or Data Analytics, this video will equip you with practical Pandas skills that professionals use every day. 🚀

📌 Don’t forget to like, share, and subscribe for more full courses on Data Science, AI, Machine Learning, and beyond!

#PandasCourse #LearnPandas #PandasTutorial #PythonDataAnalysis #SheryiansAISchool #PythonForDataScience #FreePandasCourse #sheryianscodingschool

00:00 - 00:25 - Intro
00:25 - 02:24 - Origin story of Pandas
02:24 - 03:32 - Table of content
03:32 - 11:27 - Pandas Series
11:27 - 35:20 - Dataframes in Pandas
35:20 - 45:33 - Missing Data
45:33 - 57:46 - Merging Joining and concatination
57:46 - 01:08:02 - GroupBy and Aggregation
01:08:02 - 01:17:20 - Pivot Tables
01:17:20 - 01:24:47 - Operations
01:24:47 - 01:27:58 - Finding Data
01:27:58 - 01:56:19 - Feature Extraction Project
01:56:19 - 02:23:16 - Data Capstone Project
02:23:16 - 02:23:37 - Outro]]>8618falsefullhttps://www.spreaker.com/episode/complete-data-science-course-for-beginners-numpy-sheryians-ai-school--74883320Welcome to the Complete NumPy Course!
In this 2-hour full tutorial, we’ll take you from absolute beginner to mastering NumPy — the backbone library for Data Science, AI, and Machine Learning!

What you’ll learn in this course: ✅ Basics of NumPy and why it’s powerful
✅ Creating and manipulating arrays
✅ Array indexing, slicing, and iteration
✅ Mathematical operations with NumPy
✅ Working with multi-dimensional arrays
✅ Real-world mini projects with NumPy
✅ And much more to make you job-ready!

🔥 Source Code – https://github.com/AkarshVyas/Numpy-Youtube

Whether you're starting your data science journey or building a strong Python foundation, this one video will make you confident with NumPy in just 2 hours! 🚀

📌 Don’t forget to like, share, and subscribe for more full courses on Data Science, Machine Learning, AI, and beyond!

#NumPyCourse #LearnNumPy #NumPyTutorial #PythonDataScience #SheryiansAISchool #PythonForBeginners #FreeNumPyCourse #sheryianscodingschool

00:00 - 00:28 - Introduction
00:28 - 17:18 - Notebooks
17:18 - 19:28 - Origin story of NumPy
19:28 - 46:57 - NumPy Arrays
46:57 - 01:04:12 - Arrays Indexing and Slicing
01:04:12 - 01:30:01 - Array operations
01:30:01 - 01:59:34 - NumPy Exersise
01:59:34 - 02:00:00 - Outro]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119678037Mon, 28 Apr 2025 14:00:53 +0000fertInstructor in this video - Akarsh vyas Welcome to the Complete NumPy Course! In this 2-hour full tutorial, we’ll take you from absolute beginner to mastering NumPy — the backbone library for Data Science, AI, and Machine Learning! What you’ll learn...Welcome to the Complete NumPy Course!
In this 2-hour full tutorial, we’ll take you from absolute beginner to mastering NumPy — the backbone library for Data Science, AI, and Machine Learning!

What you’ll learn in this course: ✅ Basics of NumPy and why it’s powerful
✅ Creating and manipulating arrays
✅ Array indexing, slicing, and iteration
✅ Mathematical operations with NumPy
✅ Working with multi-dimensional arrays
✅ Real-world mini projects with NumPy
✅ And much more to make you job-ready!

🔥 Source Code – https://github.com/AkarshVyas/Numpy-Youtube

Whether you're starting your data science journey or building a strong Python foundation, this one video will make you confident with NumPy in just 2 hours! 🚀

📌 Don’t forget to like, share, and subscribe for more full courses on Data Science, Machine Learning, AI, and beyond!

#NumPyCourse #LearnNumPy #NumPyTutorial #PythonDataScience #SheryiansAISchool #PythonForBeginners #FreeNumPyCourse #sheryianscodingschool

00:00 - 00:28 - Introduction
00:28 - 17:18 - Notebooks
17:18 - 19:28 - Origin story of NumPy
19:28 - 46:57 - NumPy Arrays
46:57 - 01:04:12 - Arrays Indexing and Slicing
01:04:12 - 01:30:01 - Array operations
01:30:01 - 01:59:34 - NumPy Exersise
01:59:34 - 02:00:00 - Outro]]>7200falsefullhttps://www.spreaker.com/episode/python-full-course-for-beginners-to-advanced-12-hours-complete-tutorial-python-book--7488335112-hour course, beginner-friendly, project-based, with FREE Python
Book included. No prior experience needed. | Complete 12-Hour Python Course (2026)

👨‍💻 Instructor: Akarsh Vyas | Sheryians AI School
🎁 Free Python Book: https://drive.google.com/file/d/1dUp1oxauLRrACJWvKwFqP8Bvh1NNF12c/view?usp=sharing
💻 Source Code: https://github.com/AkarshVyas/Python-Youtube
🏦 Bank Management Project: https://github.com/AkarshVyas/Bank-Management
📂 File Handling Project: https://github.com/AkarshVyas/File-handling-Youtube

---------------

This is the only Python tutorial you'll ever need. Whether you're a
complete beginner starting your coding journey, a student preparing
for placements, or someone switching careers into tech, this 12-hour
Python full course covers everything from basic syntax to OOPs,
File Handling, Data Structures, Exception Handling, and real-world
projects.

Taught in Hindi/Hinglish. 100% free. No paid course required.

---------------

✅ What You'll Learn:

→ Python installation & environment setup
→ Variables, data types & type conversion
→ Strings, operators & input/output
→ If-Else conditions & decision making
→ Loops — For, While + pattern questions
→ Functions & scope
→ Data Structures — List, Tuple, Set, Dictionary
→ Exception handling & error management
→ File handling + real-world file project
→ Object Oriented Programming (OOP) — classes, objects, inheritance
→ Advanced Python concepts
→ OOPs project + Bank Management project

---------------

🎯 This course is perfect for:
✔ Students learning Python for the first time
✔ B.Tech / BCA / MCA students preparing for exams
✔ Job seekers building Python skills for interviews
✔ Anyone switching to Data Science, AI or ML

---------------

⏱️ Course Timeline:

00:00 – Introduction & course overview
02:13 – Python history & origin
04:47 – How Python works internally
06:19 – Installation & VS Code setup
15:32 – Comments & variables
25:19 – Data types in Python
34:28 – Strings & type conversion
51:49 – Input & output in Python
59:11 – Operators in Python (all types)
01:39:27 – If-Else & conditional statements
02:16:14 – Loops concept in Python
02:50:19 – For loop questions & practice
03:40:37 – While loop questions & mini game
04:06:22 – Functions in Python
04:30:35 – Data structures overview
04:33:38 – Lists in Python
05:17:00 – Tuples in Python
05:26:10 – Sets in Python
05:49:31 – Dictionaries in Python
06:23:24 – Exception handling
06:43:23 – File handling basics
06:52:30 – File handling project
07:24:17 – Object Oriented Programming (OOP)
09:18:32 – Advanced Python concepts
10:05:09 – OOPs project — Bank Management System
11:34:50 – Outro & next steps

---------------

📺 Related Videos:
→ Full Stack Gen AI Project (React + Node + Gemini) — youtu.be/zG3hNL08Dro
→ Why 90% Coders Never Become Developers — youtu.be/9uWBy6f97Oo
→ Complete Python Playlist — youtube.com/playlist?list=PLaldQ9PzZd9qPYGj4aWUXitBlfWz72e9m

---------------

🌐 Website: https://sheryians.com/
🎓 All Courses: https://sheryians.com/courses
📷 Instagram: https://www.instagram.com/sheryians_coding_school/
💌 Telegram: https://t.me/sheryiansCommunity
🎮 Discord: https://discord.gg/Au3TquBarQ
💼 LinkedIn: https://in.linkedin.com/company/the-sheryians-coding-school
📘 Facebook: https://www.facebook.com/sheryians.community

Peace out ✌

#Python #LearnPython #PythonFullCourse #SheryiansCodingSchool #PythonHindi #PythonForBeginners #PythonCourse #DataScience #AI #Coding #Programming #PythonTutorial2026 #PythonforDataScience #PythonProgramming #PythonProjects]]>https://app.pigeonpod.cloud/feed/2095303123399610369/episode/2095303190119677966Wed, 23 Apr 2025 13:30:27 +0000fertLearn Python from absolute zero to advanced level in one complete 12-hour course, beginner-friendly, project-based, with FREE Python Book included. No prior experience needed. | Complete 12-Hour Python Course (2026) 👨‍💻 Instructor: Akarsh Vyas |...12-hour course, beginner-friendly, project-based, with FREE Python
Book included. No prior experience needed. | Complete 12-Hour Python Course (2026)

👨‍💻 Instructor: Akarsh Vyas | Sheryians AI School
🎁 Free Python Book: https://drive.google.com/file/d/1dUp1oxauLRrACJWvKwFqP8Bvh1NNF12c/view?usp=sharing
💻 Source Code: https://github.com/AkarshVyas/Python-Youtube
🏦 Bank Management Project: https://github.com/AkarshVyas/Bank-Management
📂 File Handling Project: https://github.com/AkarshVyas/File-handling-Youtube

---------------

This is the only Python tutorial you'll ever need. Whether you're a
complete beginner starting your coding journey, a student preparing
for placements, or someone switching careers into tech, this 12-hour
Python full course covers everything from basic syntax to OOPs,
File Handling, Data Structures, Exception Handling, and real-world
projects.

Taught in Hindi/Hinglish. 100% free. No paid course required.

---------------

✅ What You'll Learn:

→ Python installation & environment setup
→ Variables, data types & type conversion
→ Strings, operators & input/output
→ If-Else conditions & decision making
→ Loops — For, While + pattern questions
→ Functions & scope
→ Data Structures — List, Tuple, Set, Dictionary
→ Exception handling & error management
→ File handling + real-world file project
→ Object Oriented Programming (OOP) — classes, objects, inheritance
→ Advanced Python concepts
→ OOPs project + Bank Management project

---------------

🎯 This course is perfect for:
✔ Students learning Python for the first time
✔ B.Tech / BCA / MCA students preparing for exams
✔ Job seekers building Python skills for interviews
✔ Anyone switching to Data Science, AI or ML

---------------

⏱️ Course Timeline:

00:00 – Introduction & course overview
02:13 – Python history & origin
04:47 – How Python works internally
06:19 – Installation & VS Code setup
15:32 – Comments & variables
25:19 – Data types in Python
34:28 – Strings & type conversion
51:49 – Input & output in Python
59:11 – Operators in Python (all types)
01:39:27 – If-Else & conditional statements
02:16:14 – Loops concept in Python
02:50:19 – For loop questions & practice
03:40:37 – While loop questions & mini game
04:06:22 – Functions in Python
04:30:35 – Data structures overview
04:33:38 – Lists in Python
05:17:00 – Tuples in Python
05:26:10 – Sets in Python
05:49:31 – Dictionaries in Python
06:23:24 – Exception handling
06:43:23 – File handling basics
06:52:30 – File handling project
07:24:17 – Object Oriented Programming (OOP)
09:18:32 – Advanced Python concepts
10:05:09 – OOPs project — Bank Management System
11:34:50 – Outro & next steps

---------------

📺 Related Videos:
→ Full Stack Gen AI Project (React + Node + Gemini) — youtu.be/zG3hNL08Dro
→ Why 90% Coders Never Become Developers — youtu.be/9uWBy6f97Oo
→ Complete Python Playlist — youtube.com/playlist?list=PLaldQ9PzZd9qPYGj4aWUXitBlfWz72e9m

---------------

🌐 Website: https://sheryians.com/
🎓 All Courses: https://sheryians.com/courses
📷 Instagram: https://www.instagram.com/sheryians_coding_school/
💌 Telegram: https://t.me/sheryiansCommunity
🎮 Discord: https://discord.gg/Au3TquBarQ
💼 LinkedIn: https://in.linkedin.com/company/the-sheryians-coding-school
📘 Facebook: https://www.facebook.com/sheryians.community

Peace out ✌

#Python #LearnPython #PythonFullCourse #SheryiansCodingSchool...]]>41716falsefull