From Reddit comment by u/mpt977262 regarding the "bogus" course InspiritAI, and better resources for learning artificial intelligence and machine learning (AI/ML) below:
Amazing, free, high-quality ML education is easy to find online; there's in fact too much out there and it's hard to know which ones to stick by. The ones that I have used and can personally attest to are the following:
- Andrew Ng's Coursera courses (https://www.coursera.org/collections/machine-learning): these are the classic ML courses that many people swear by. I skipped my college ML courses and just watched these myself). I'd recommend starting with "Machine Learning for Everyone" (https://www.coursera.org/specializations/machine-learning-introduction). The other courses are built on top of that and will give you comprehensive theory as well as in-depth guided projects.
- fast.ai: This is so good it feels illegal that it's free. Great applied introduction to deep learning. For the coding-inclined, the deep dive course into neural nets is in https://course.fast.ai/. In post-grad ML projects, I've found myself referencing fast.ai because I think to myself "I feel like I remember seeing how to do this in some lesson from fast.ai".
freeCodeCamp: https://www.youtube.com/@freecodecamp is a YouTube channel consisting of long-form (think 4-8+ hours) tutorials on various topics in programming, ML, networking, math, literally anything that a computer can do. I would've learned more applicable knowledge spending 1 year deep-diving and doing as many tutorials as I could from freeCodeCamp than I did from my 4-year Ivy League degree.
Kaggle (https://www.kaggle.com/): You want to learn ML? Start building ML stuff. This is a competition website where people build ML projects (e.g., "classify these images with ML") to see who gets the highest score. Amazing array of free tutorials. Great open-source community. You got a question? Ask in the forums.