The timing of the course also couldn’t have been better for me personally. It was released about 2 weeks after I quit my job. I wanted to learn how to build digital products, and after struggling with scattered tutorials, CS 253 was like being thrown a life preserver.
I enjoyed that course by the way.
I have not taken this course, but have watched the excerpts particularly about reddit. I was definitely impressed with the presentation and have no difficulty believing the entire course is quite good
The only online course I've undertaken, so of course it's the best one. But it's exceptionally well made, it's up to date, teaches about a wide area of machine learning and AI field. Not just the theory, but about Kaggle, how professional AI designers work, what they do, "what it's all about", and so forth. The community is helpful, the forums are active. All free btw. Very good!
CS50 (https://www.edx.org/course/cs50s-introduction-computer-scien...) - Best Intro to Computer Science
Nand2Tetris I and II (https://www.coursera.org/learn/build-a-computer) - Build a computer from logic gates up to a compiler, this is the best class I've ever taken.
Agile Development Using Ruby on Rails (https://www.edx.org/professional-certificate/agile-developme...) - Great introduction to web development and software engineering principles
I've also been reading some technical books. Would definitely recommend
Modern Operating Systems - Tanenbaum
Designing Data-Intensive Applications - Kleppmann
Barbara Oakley's Learning How To Learn class  was immensely helpful for understanding how brains work and how I could learn efficiently.
I made it through college with a combination of cramming and bad sleep habits, but focusing on spaced repetition, the diffuse/active modes, and sleep has made classes I've taken since feel like easy mode.
Added a lot of clarity to my process of thinking.
Highly recommend as well (I did not take the course, though, just found the book by accident).
Probably a type of 'self-awareness' of own's thinking process does not start before 11.
But it WAS the best introduction to software development I have ever seen, and I have seen quite a few.
I did see a couple of people quit the course because it was "too complicated" - in reality, it's just complicated enough, and the progression is natural and well-presented.
I've converted all 30 videos into blog format (with live code samples) here https://www.discoverdev.io/blog/series/js30/
This YouTube series (in fact his channel in general) makes construction look simple, accessible and rewarding. He explains theory while demonstrating practice, and the end result is not abstract knowledge but a real building that can house all manner of other physical (and digital) projects.
Firm grounding in the Central Dogma. Covers the entire history of genetics. From Gregor Mendel's peas. To Morgenstern's Fruit Fly Lab. And right up to the present day Supreme Court BRCA case and CRISPR/Cas9. Essential background for understanding the coming century of New Biotech.
This makes a statistical tool accessible and useful to people who have no stats training. It explains why SPCs are usually better than the widely used RAG charts.
This is a real Caltech course, not a made-for-online offering. When I took it, we shared the online forum with undergrads taking the class on campus, and Professor Abu-Mostafa was incredibly responsive to all kinds of questions.
The course covers the theory and mathematics behind various machine learning techniques. It's not a practical course that just teaches you to use some particular library.
Then I decided to check it out.
While the production quality is out of the 1990s and it starts off pretty dry, there is a lot of great content and applicable techniques here, if you stick with it a little bit.
Fast.ai has an incredible library built on PyTorch and it’s amazing when he talks about the latest research and already has it available for free there. The teaching style is super nice too, very practical and without skipping the bits that get you to world class results.
course page: http://online.stanford.edu/course/startup-engineering and http://startup.stanford.edu/
course videos: https://www.youtube.com/playlist?list=PL58C6Q25sEEFVyISrZc80....
if i worked in a team again, i would probably make this a required course for new hires, no matter how much experience. it isn't hard, but i've seen the occasional experienced engineer complain it's too easy and beneath them, and then fail badly on the later stages - hmm, maybe they're lying about the experience. come to think of it, it'd probably be great in an interview, too.
This opens the curtains to what happens behind a website and provides data for every discussion in marketing/product/etc. Taking this when I was 18 years old literally kickstarted my career.
https://www.coursera.org/learn/solar-system - i think it's still free, right?
Unit 1: Water on Mars - 3 weeks
Unit 2: The insides of giant planets - 2 weeks
Unit 3: Big questions from small bodies - 2 weeks
Unit 4: Life in the solar system - 2 weeks
Excellent course; he is a fantastic teacher.
Cs50 - Twitch
Building a truly great course is pretty difficult.