
Ask HN: Best Online Courses? - ambivalents
I searched but there hasn&#x27;t been a thread about this in a while.<p>What is the best online course you&#x27;ve taken? Doesn&#x27;t have to be confined to CS -- I&#x27;m personally interested in expanding my horizons and learning new things in different fields.<p>Thanks all.
======
yesenadam
Sapolsky - _Biology of Human Behavior_ 25 lectures
[https://www.youtube.com/watch?v=NNnIGh9g6fA&list=PL848F2368C...](https://www.youtube.com/watch?v=NNnIGh9g6fA&list=PL848F2368C90DDC3D)

It's accessible to laymen, no prior knowledge needed. It covers so many
different fields and levels of knowledge ("buckets" Sapolsky calls them),
different ways of explaining human behaviour. By the signals in their brain,
or the hormones in their blood, or what happened that day, or their childhood,
or their genes, or evolution of humans etc. Also looks at other animals. A lot
of touching/funny/inspiring/poignant stories about scientists in the field(s).
Sapolsky is an amazing lecturer/raconteur.

Hamming - _Learning to Learn_ 32 lectures
[https://www.youtube.com/watch?v=AD4b-52jtos&list=PL2FF649D0C...](https://www.youtube.com/watch?v=AD4b-52jtos&list=PL2FF649D0C4407B30)

The famous "You and your research" is one lecture in this, but every one of
them is fascinating. History of computers, AI, codes, n-space, digital filters
etc etc. Mainly it's great seeing how his mind works, his thinking style.
(I've since read a few of his books, and I love how they're soaked with
practical experience, in the same way these talks are. It's all stuff he's
_lived_.)

~~~
hhs
Nice question, ambivalents, and thanks for the recommendation, yesenadam. Very
cool. I just started watching the first video of Sapolsky's lecture and found
it to instantly capture my attention. I'm going to stick to this series. By
the way, studying Sapolsky could also help with the forum question recently in
Ask: HN about explaining things well to people.

His lectures look like a neat place to get a deep anthropological grip on
things.

------
otras
I've taken a few, and these two are my favorites:

 _Learning How to Learn_ by Barbara Oakley:
[https://www.coursera.org/learn/learning-how-to-
learn](https://www.coursera.org/learn/learning-how-to-learn) Hands down the
biggest return on investment for an online class. It helped my future learning
_so much_. Highly, highly recommend it.

Harvard's _CS50_ : [https://www.edx.org/course/cs50s-introduction-computer-
scien...](https://www.edx.org/course/cs50s-introduction-computer-science-
harvardx-cs50x) Took this course when learning to program. It was difficult,
but I learned a great deal. Fantastic professor, good problem sets, and great
production value.

~~~
throwaway123x2
Was learning how to learn actually that useful? I kinda let off halfway
through it ...

~~~
otras
I would say that it wasn't watching the videos that was helpful, but more
applying the concepts and techniques. I took general notes and reviewed them
periodically (spaced repetition!), and I applied the general ideas to my
classwork.

It's kind of like learning math. During a lecture, it's easy to think to
yourself "OK, I understand this," but you learn so much when working through
practice problems. I found myself saying "OK, that makes sense" when watching
the LHTL videos, but I really saw the benefit when actively working on
applying spaced repetition, diffuse vs focus mode, getting sleep, and other
strategies to my studying. I was taking a few post-graduate CS classes at the
time, and compared with my study skills and results from undergraduate, it
felt like magic to study efficiently and get good results.

------
Sidious
Previously:

[https://github.com/prakhar1989/awesome-
courses#readme](https://github.com/prakhar1989/awesome-courses#readme)

[https://hn.academy/](https://hn.academy/)

------
aregsarkissian
"The great courses" (google it) has a many well done courses taught by college
professors on a variety of topics

------
bjourne
Udacity courses: Applied cryptography, Intro to Theoretical Computer Science

Coursera courses: Digital Signal Processing

and Khan Academy.

