AI: It’s here, it’s there, it’s seemingly everywhere in 2025. How ubiquitous is it? Well, 58% of businesses that started using AI cited “pressure from competitors” as the reason why, according to Tech.co’s own research.
Granted, that might be a warning sign more than an indication that AI is genuinely too big to fail. But we can’t stand around waiting for an AI bubble to collapse. With a dismal labor market continously worsened by waves of layoffs, millions of white collar workers are wondering how to keep their jobs or find a better one.
The answer might be upskilling. If you’re interested in gaining a few skills surrounding generative AI, look no further. Here, we’ve rounded up the best free online courses that can give you the edge when to comes to talents like prompting, research, or integrating AI tools into your workflow. At the very least, spending a few hours of your time listening to a lecture series should take your mind off of the uneasy future of work.
IBM: Data Science Professional Certificate
⏰Length: 120 hours
IBM offers the longest course in this guide, by far, with this series aimed at preparing students for a career as a data scientist. That’s because it’s a whole suite of courses bundled together, and all offered online for no cost at all.
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Those courses include: “What is Data Science?,” “Tools for Data Science,” “Data Science Methodology,” “Data Analysis with Python,” and “Data Analysis with Python,” among others. You’ll get a total of 12 courses, with most clocking in at over ten hours each.
This series isn’t limited just to artificial intelligence, but it definitely devotes plenty of time to the concept. A few AI-specific courses include “Machine Learning with Python,” and one explicitly about upskilling your existing data scientist vocation, called “Generative AI: Elevate Your Data Science Career.”
Granted, it’s a big time and energy investment. But why take a piecemeal approach to learning? If it’s a natural fit for your interests, IBM’s course might be able to take your career in a whole new direction.
Sign up for the whole series — or any individual course you’re interested in — here on Coursera.
UW: Machine Learning Specialization
⏰Length: 80 hours
The University of Washington’s course on machine learning can take you from the basics to mastering the core machine learning fundamentals. It’ll cover topics including Regression, Classification, and Clustering and Retrieval, as well as the case studies you’ll need to get some practical understanding of the concepts.
According to the course itself, you will “learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.” As with the IBM courses, the programming language of choice is the general-purpose option Python.
You’ll need to have a little experience with computer programming to start this one, but it’s a great way to buckle down and start getting familiar with machine learning, the term for computer systems that adapt themselves by learning from data. At a pace of about ten hours a week, it should take you two months to complete.
Check it out here on Coursera.
AdelaideX: Ethical AI for Students
⏰Length: 8 hours
Maybe you’re not looking to start an entirely new career, or develop your computer language fluency. Try this option for a shorter course that you can handle in the evenings across a week or two: It’s a guide to some of the ethical questions behind the use of AI, and it’ll only take you 8 hours, start to finish.
Those questions will include the consequences of using incorrect or biased information created by generative AI, but they also cover the right and wrong ways to cite the use of AI, and potential future AI developments in AI.
You’ll also pick up some related soft skills like the ability to determine when something has been AI-generated (we have some tips on how to detect an AI image ourselves), and how to identify differences in the usage protocols of different policies, as well as general terminology.
Far more ink has been spilled on the challenges of AI ethics, from copyright theft to climate change impacts, but this course sticks to a simple goal. By the time you’re done, you should be able to produce unbiased, accurate, and transparent AI content. This one’s available on edX.org, so head over to that online learning website to get started today.
HP: Generative AI Mastery: Revolutionizing Game Development
⏰Length: 15 hours
Sometimes you need a fun topic before your brain actually enjoys learning enough to actually retain the information. Enter this game development course, which offers an insight into the ways in which generative AI is transforming the gaming industry.
Granted, actual game development isn’t all fun and, uh, games. Here, you’ll be taking a look at AI’s impact on areas including narrative, concept art, texturing, modeling, and animation. How can AI help build visuals and stories within these topics? It’ll take you 15 hours to find out.
The course will introduce you to the basics of Unreal Engine 5 and Unity 3D, with sessions covering topics including “Basic C# Scripting for Unity 3D,” as well as AI-focused looks at everything from character modeling to music creation. Check it out on edX.org now.
Codeacademy: Learn How to Use AI for Coding
⏰Length: 1 hour
We opened this list with a months-long career-shaping series. Now, consider the opposite amount of energy investment: Here’s a course you can complete over a single lunch break. Don’t say we don’t have range here at Tech.co HQ.
This Codeacademy course will offer the most basic possible guide to the intersection of AI and coding. Sure, AI can craft functional code snippets and syntax. But do you know which tasks you can trust it to handle and which ones need a human touch? What about how to write the prompts to get the results you need? AI tools might be time-savers, but knowing how to use them rapidly becomes almost as big a challenge as writing the code yourself.
This quick free course covers “the generation of Bash commands, regular expressions, and database queries, [as well as] generating classes and unit tests to ensure code quality and reliability and refactoring code to improve readability and maintainability.”
When you’re done, you’ll have a project and two quizzes to test your knowledge. Check it out on Codeacademy here.
Getting to Grips With AI
If you’re just trying to understand the modern technology landscape, hopefully this grab-bag of AI courses can help. If you own or manage your own small business, there’s one last guide that might be worth taking a look at: Our new explainer on how to think about and create your own AI policy — the business-specific guidelines that determine what AI models your employees are or aren’t allowed to use, and what type of data they input.
Some companies ban AI entirely, while others allow certain models. But many more haven’t thought about AI in that level of detail at all. According to Tech.co’s 2025 report on the Impact of Technology on the Workplace, 35% of businesses don’t regulate employee chatbot use at all.
Take your time getting familar with the ethical implications — and the cybersecurity risks — of AI use, as well as its many potential applications across your industry. Then, make sure your company has issued an AI policy before it runs afoul of any AI pitfalls out there.
