I'm finding the current MOOCs sites to became very bloated due to the high number of courses. Now it is difficult to find the good ones. Which are your favorites?
If you don't mind missing the "M" part of MOOCs, you can learn a lot from university courses. Most of the top CS schools have slides and homeworks on their course websites.
These courses have all been through the test of time and are specifically designed to provide an in-depth education with material written by some of the best and brightest educators in the field.
You can simply follow along with the material at your own pace. Occasionally you'll come across something that you can't do (e.g. part of the assignment requires running tests on the school's private cluster), but most of the homeworks you can implement on your own. The only downside is there's nowhere to ask questions if you really get stuck (don't go contacting the course staff...), but with unlimited time you can usually figure it out eventually.
> The only downside is there's nowhere to ask questions if you really get stuck
Well, there's always stackexchange.
Finding open university courses can be a bit tricky. For that, MIT open courseware is amazing. After self-studying a course there, I have to say the depth is so much better than any MOOC I've ever done. No lecture videos though, but for me that's not a problem.
computer science is an extremely broad area. Narrow it down, maybe?
1. Introduction to Computational Thinking at MIT was a great one.
2. Robert Ghrist has the best set of SV Calculus courses on Coursera.
3. Gilbert Strang's LA courses are the best.
4. For Algorithms course, I would recommend Sedgewick and Wayne's course on Coursera.
5. For PL course, go with the WashU course on Coursera.
6. For Machine Learning, you should start with Andrew Ng's Machine Learning.
7. Cryptography I, II by Dan Boneh is a great one.
8. Introduction to Programming with Python at MIT on edX is a good course. And so is CS50 by David J. Malan.
9. The nand2tetris course on Coursera.
These are some that I can vouch for. You did not mention your level or what topic you want to learn.
The best way is to do a google search for moocs, and try several of them out, and pick one with the teacher whose teaching style you like the most.
In MOOCs that are not mandated, the personality of the teacher matters a lot. In my opinion- it is the most important factor.
You should also look up courses where all materials are publicly available- tests, assignments, homework problems, etc. If some parts are not, you can always email a prof, and they will almost never turn you down.
Follow discussions on Reddit. Engage in discussions, too.
You should look up https://teachyourselfcs.com and check out the recorded courses there. Do the ones that you would like.
Yes, the Sedgewick course is filled with wisdom. Even if someone has done an algo course before, or someone do not want to do the exercises, the videos are very worth watching- even like a documentary or movie.
One will grow after watching those videos.
And Strang is amazing. He does so much with a chalk and blackboard that many with advanced graphics and stuff fail to do.
For example, if you want to learn...
Artificial Intelligence (Stanford): https://stanford-cs221.github.io/autumn2021/
Programming Languages (UW): https://sites.google.com/cs.washington.edu/cse341spring2021/...
Distributed Systems (MIT): http://nil.csail.mit.edu/6.824/2021/schedule.html
These courses have all been through the test of time and are specifically designed to provide an in-depth education with material written by some of the best and brightest educators in the field.
You can simply follow along with the material at your own pace. Occasionally you'll come across something that you can't do (e.g. part of the assignment requires running tests on the school's private cluster), but most of the homeworks you can implement on your own. The only downside is there's nowhere to ask questions if you really get stuck (don't go contacting the course staff...), but with unlimited time you can usually figure it out eventually.