https://www.nexford.edu/enBusinessCopyright Daniel Hayeshttps://d3wo5wojvuv7l.cloudfront.net/t_rss_itunes_square_1400/images.spreaker.com/original/b81d79d9e4be46e3fa58df8702a564a0.jpghttps://www.nexford.edu/Sat, 24 Oct 2026 11:59:19 +0000Daniel HayesDaniel Hayesfeeds@spreaker.comAI Skills at Work is about turning what you hear about AI into skills you can actually use at work. We break down applied AI, automation, and data skills for professionals who want to move from following the AI conversation to contributing to it.false173c8953-4ee1-5930-8e5d-59af797938cbepisodichttps://www.spreaker.com/episode/turning-what-you-hear-about-ai-into-skills-you-can-use-at-work--75963246Why staying informed only goes so far
Regular listening and reading build awareness. You learn which tools are emerging, how companies talk about automation, and where the risks sit. That context is valuable, and it is worth keeping.
The gap appears when you are asked to act. A manager wants to know whether a process can be automated. A team needs data cleaned before a decision. A proposal requires someone to weigh cost, ethics, and feasibility at once. These tasks call for practice, feedback, and a clear sequence of skills that build on each other.
Structured learning closes that gap by asking you to produce something. You write the query, run the script, map the workflow, and explain your reasoning to someone else. Each step turns an idea you have heard into a skill you can repeat.
What an applied AI degree can add
A degree that blends business and AI gives that practice a direction. The online BS Artificial Intelligence Business Nexford offers is one example of this approach. Nexford University pairs business foundations in strategy, finance, operations, and marketing with applied work in Python, SQL, cloud services, automation, and machine learning. The aim is not to turn learners into engineers. Instead, it prepares them to bridge technical teams and business decision makers, a role the program calls the AI Translator.
For you, this means each topic connects back to a workplace use. Programming is taught for retrieving, cleaning, and analyzing business data. Data storytelling focuses on presenting findings so non-technical colleagues can act on them. Governance and ethics run through the program, so you learn to question how AI is deployed, not only how it works. The degree finishes with a capstone project built around a real business challenge, giving you a portfolio piece that shows employers what you can do.
Fitting study around work and life
Most working adults cannot pause their careers to study. The program is fully online, and learners pay per course and move at their own pace. You begin with one course at a time for your first seven courses, then can take on two at a time as you find your rhythm. A digital badge is earned for each completed course, so you have visible progress to share long before graduation.
This structure suits people who already learn in short, regular sessions. You can treat study the way you treat any steady habit: consistent effort, reviewed often, and applied quickly.
Staying curious about AI is a strong foundation. The next step is building skills you can apply with confidence. If you are ready to move from following the conversation to contributing to it, a structured and practical program is a sensible place to begin.
]]>https://api.spreaker.com/episode/75963246Sat, 24 Oct 2026 11:59:05 +0000Daniel HayesMany professionals now follow AI closely. They read newsletters, listen to expert interviews, and save useful ideas to revisit later. Yet a common question follows: how do you move from understanding AI in conversation to using it with confidence in...Why staying informed only goes so far
Regular listening and reading build awareness. You learn which tools are emerging, how companies talk about automation, and where the risks sit. That context is valuable, and it is worth keeping.
The gap appears when you are asked to act. A manager wants to know whether a process can be automated. A team needs data cleaned before a decision. A proposal requires someone to weigh cost, ethics, and feasibility at once. These tasks call for practice, feedback, and a clear sequence of skills that build on each other.
Structured learning closes that gap by asking you to produce something. You write the query, run the script, map the workflow, and explain your reasoning to someone else. Each step turns an idea you have heard into a skill you can repeat.
What an applied AI degree can add
A degree that blends business and AI gives that practice a direction. The online BS Artificial Intelligence Business Nexford offers is one example of this approach. Nexford University pairs business foundations in strategy, finance, operations, and marketing with applied work in Python, SQL, cloud services, automation, and machine learning. The aim is not to turn learners into engineers. Instead, it prepares them to bridge technical teams and business decision makers, a role the program calls the AI Translator.
For you, this means each topic connects back to a workplace use. Programming is taught for retrieving, cleaning, and analyzing business data. Data storytelling focuses on presenting findings so non-technical colleagues can act on them. Governance and ethics run through the program, so you learn to question how AI is deployed, not only how it works. The degree finishes with a capstone project built around a real business challenge, giving you a portfolio piece that shows employers what you can do.
Fitting study around work and life
Most working adults cannot pause their careers to study. The program is fully online, and learners pay per course and move at their own pace. You begin with one course at a time for your first seven courses, then can take on two at a time as you find your rhythm. A digital badge is earned for each completed course, so you have visible progress to share long before graduation.
This structure suits people who already learn in short, regular sessions. You can treat study the way you treat any steady habit: consistent effort, reviewed often, and applied quickly.
Staying curious about AI is a strong foundation. The next step is building skills you can apply with confidence. If you are ready to move from following the conversation to contributing to it, a structured and practical program is a sensible place to begin.
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