How do you know what AI course to look for?

Search "best AI course" and you'll get a list ranked by brand recognition: Stanford, Google, IBM, whoever bought the top ad slot. None of that tells you whether a course fits how you actually work, learn, or have time to show up. A highly rated course aimed at software engineers is close to useless for a marketing manager who's never opened a terminal, and a brilliant beginner course will bore someone who already codes.

Before you look at a single course, it's worth answering six questions about yourself. They're the same six we ask in our own matching quiz, not because we invented them, but because they're the six things that actually change which course is right.

1. What do you actually do all day?

Not your job title, your actual work. "Marketing manager" could mean someone who writes copy all day or someone who mostly runs meetings. A course built for developers will spend its first three modules on things a business analyst never needs, and a business-focused course will feel thin to someone who already writes Python. Be honest about whether you code regularly, work mostly in spreadsheets and dashboards, or spend your day in meetings and strategy. That alone rules out a large chunk of any course catalogue.

2. Where are you starting from?

Not "am I smart enough," but literally: have you used ChatGPT a handful of times, or have you already built something with an API? Courses are pitched at a level, and the gap between "complete beginner" and "comfortable with the basics" is bigger than most course pages let on. Starting a course two levels above where you are is the single most common reason people quit partway through.

3. What are you actually trying to achieve?

Learn a skill for your current job, switch careers entirely, get a certificate for your resume, or just understand what all the fuss is about? These want different courses. A career-switch goal needs depth, structure and ideally a credential. Curiosity needs something short and cheap. Conflating the two is how people end up either overpaying for a twelve-week bootcamp they didn't need, or under-investing in a taster course that won't get them hired.

4. What can you actually spend?

Not "what's it worth," what's genuinely available. Free courses from MIT OpenCourseWare or fast.ai are as rigorous as anything paid, they just come without hand-holding or a certificate. Paid courses buy you structure, support and sometimes a credential that matters to employers. Neither is universally right, it depends on whether you value the credential or the outcome more.

5. How much time do you honestly have?

Most people wildly overestimate this. Be realistic about hours per week, not what you'd like it to be. A course that assumes ten hours a week will sit unfinished if you only have three. Shorter, lower-intensity courses have a much higher completion rate for busy people, and a course you actually finish beats a better course you abandon in week two.

6. How do you actually learn?

Video lectures, hands-on projects, reading, or a structured cohort with deadlines and other people to keep you accountable. Some people need the external structure of a cohort to finish anything; others find it slows them down. This is the most overlooked factor, and often the one that decides whether you finish at all.

Put it together, then look

Once you know your answers to those six things, that becomes your filter. A comfortable-beginner marketing manager who wants a career switch, has $200 to spend, four hours a week, and learns best from structured video, has maybe eight or nine genuinely good matches out of hundreds of courses on the market. Everything else is noise for that person, however good it is for someone else.

You can work through this manually against course pages, or answer the same six questions in our free matching quiz and see it done for you against 77 courses in about a minute.