Learning how to learn from coursera is my all time favourite. I have gone over the course material a few times just to make sure I don't forget all the things the professors talk about.
https://learngitbranching.js.org/ - this was posted recently again. it's not perfect, and isn't going to completely de-mystify git. but it's a great exercise and seems to clear up a thing or two.
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.
I tried this a while back, and I am so confused by the rebasing part I figured I'd find something else. As someone who knows some git, but only has to used it every once in a while, this website does not help me..
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.
I really enjoyed the famous Andrew Ng's machine learning course on Coursera. That was my first exposure to MOOC and I was amazed that such great content was available for free.
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!
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.
I took this course with someone I was teaching webdev. It wasn't the best course for me by any means because I already knew the material.
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 taken quite a few online courses, but none better than JS30 from WesBos. Really good stuff - a set of 30 videos where you create 30 small JavaScript projects. Great for people already familiar with JS and trying to get more comfortable!
I’m currently taking udacity’s AI for trading class. It’s a little pricey ($999 for the first term), but damn, it’s so good. Best class I’ve ever taken, online or otherwise.
The sadly-discontinued Udacity CS 253 (Web Application Engineering) with Steve Huffman. Partly because of the accessibility of the material and Steve’s sometimes puckish delivery (learning sick MongoDB burns in 2012 put me way ahead of the tech curve). Learning how to build and deploy a web app in Python with the super-lightweight webapp2, rolling your own salted-and-hashed account system... so many good tidbits that gave me a good intuition about how web apps are put together.
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.
Want to point out that Steve Huffman, also known as /u/spez, is co-founder and (once again) CEO of reddit.
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
Barbara Oakley's Learning How To Learn class [0] 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.
I am not an expert by any means. But asking child at, say, age 13 to read portions of it and explain back to parents, what she/he picked up from there -- will work well.
Probably a type of 'self-awareness' of own's thinking process does not start before 11.
I felt that the course was too long to cover just a few topics like spaced repetition and diffuse mode. Besides those key takeaways are pretty intuitive.
Definitely Eric Lander's Introduction to Biology - The Secret Of Life class (MITx 7.00x)
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 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.
HBX CORe, Online course from Harvard (actually more like a few courses bundled into one) that I expected to be high level managerial focused but was pleasantly surprised to be very hands on with spreadsheets and whatnot https://hbx.hbs.edu/courses/core/. Close second is Living at the Nuclear Brink by Dr. Perry (Former US Secretary of Defense) which was incredibly informative https://online.stanford.edu/courses/fsi-y0002-living-nuclear...
I've been working on a course recently [1] on Building an App from Scratch Using Ruby on Rails (not revolutionary I know, but needed to start somewhere).
Building a truly great course is pretty difficult.
Functional Programming Principles in Scala https://www.coursera.org/learn/progfun1 on Coursera. It's taught by Martin Odersky, one of the language's creators. Very well organized, highly automated assignment testing (you submit via CLI). I went in wanting to learn Scala, but what I learned about FP has stayed with me for years. Even though I've moved on from Scala I'm a much better programmer for having taken that course.
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[ 7.2 ms ] story [ 155 ms ] threadExcellent course; he is a fantastic teacher.
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.
https://improvement.nhs.uk/resources/making-data-count/
https://improvement.nhs.uk/documents/2748/NHS_MAKING_DATA_CO...
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.
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
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!
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.
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/
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.
Thanks, Steve.
I enjoyed that course by the way.
[0]: https://eu.udacity.com/course/web-development--cs253 [1]: https://www.udacity.com/course/intro-to-backend--ud171
https://youtube.com/watch?v=b2F-DItXtZs
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
Barbara Oakley's Learning How To Learn class [0] 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.
[0]: https://www.coursera.org/learn/learning-how-to-learn
https://barbaraoakley.com/books/a-mind-for-numbers/
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.
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.
https://www.edx.org/course/introduction-to-biology-the-secre...
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.
Building a truly great course is pretty difficult.
[1] https://www.nimblehq.com
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