We do this as part of our university practical course as well (2 week challenges in teams of 4, sometimes participating also in external competitions). While I agree that this good for learning, I would, however, say it is completary to lectures. It makes no sense if people just learn to overfit some hyperparams to beat a score. So rating should at least be done wisely. Otherwise I think people need lectures to understand the real limits of tech and actually find novel uses.<p>With many good lecture contents online I think it also would be good to also switch to more live competitions at university to do inverted classroom style learning. I think it is the mix that matters (along with the quality)
Every time I read a slogan like "learn X in Y weeks" or "learn through games instead of lectures", I have to think of a Peter Norvig piece: <i>Teach Yourself Programming in Ten Years</i>.<p>Honestly instead of taking paid courses that promise to teach incredibly difficult subjects in weeks, just take one of the longer courses like Andrew Ng's that start with the fundamentals and are free. Bootcamp style education is awful.<p><a href="https://norvig.com/21-days.html" rel="nofollow">https://norvig.com/21-days.html</a>
> Learn reinforcement learning in 4 weeks<p>There are so many high quality, free resources online for learning RL [1,2,...]. Four weeks of primarily self-guided M-F study isn't nearly enough time to obtain anything more than a cursory understanding of the topic. Kaggle, various gym environment baselines, and workshop competitions exist for those who want to compete.<p>[1] <a href="https://www.deepmind.com/learning-resources/introduction-to-reinforcement-learning-with-david-silver" rel="nofollow">https://www.deepmind.com/learning-resources/introduction-to-...</a>
[2] <a href="http://incompleteideas.net/book/the-book-2nd.html" rel="nofollow">http://incompleteideas.net/book/the-book-2nd.html</a>
Everytime I read something like "learn ML" I think about learning some descendant of the ML programming language like OCaml, F# or Standard ML instead of machine learning.