Disclaimer: I built Class Central
MIT Mathematics for Computer Science (harder but still not that hard):
Steve Skienna discrete mathematics course (graduate course based on Knuth's "Concrete Mathematics", quite hard):
I also recommend checking out some books:
http://infolab.stanford.edu/~ullman/focs.html - free "Foundations of Computer Science" book that combines discrete mathematics with C programming and some theory of computation stuff, a pretty good way to make things more practical
http://www.amazon.com/Discrete-Mathematics-Elementary-Beyond... - very pleasant introductory discrete mathematics book, a welcome break from the usual "brick" format and covers some important topics that often do not make it into the normal discrete mathematics curriculum e.g. induction on trees.
http://www.amazon.com/Introductory-Combinatorics-Modern-Birk... - classic introduction to combinatorics
The course reader  covers the first half of the class and is pretty good.
I'd also recommend - Engineering Mathematics by KA Stroud. All three volumes are fantastic.
I wonder if this offer stands from semester to semester, and therefore if he seeded an exploit (or several, given how the extra credit reads) or whether the whole thing is just more of his light-hearted style.
But I definitely agree: that course looks great.
Typically, I create a fresh ubuntu server at the start of each semester, and I let it go unpatched for the duration of the semester.
I might put the course online some day, but lectures are extremely interactive.
I'm not sure how well they'll translate to an online format.
 - https://www.dropbox.com/sh/zanwtoflw4pcfu8/5pdT6axS3y
 - http://matt.might.net/teaching/compilers/spring-2015/#projec...
A reasonable amount of the course material is in blog posts, and I add more posts each semester.
6006 Introduction To Algorithms from MIT
Machine Learning from Stanford:
Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.
I really enjoyed both of them. Reviews:
Course book and homework assignments are available online if anyone is interested is taking this course. :)
Pedigree and pedantics have taken precedence over hacking and creative problem solving, particularly in the Silicon Valley where a Stanfordcal degree and Googfacetwit work experience is expected.
To get the education you'll get at a college, you'll have to spend those three years studying any how. So college is really like three years of independent study and one year of class time.
Why not just spend that year of time going to classes, learning things from professors (some of whom are quite knowledgeable, and doing cutting edge CS theory research), learning things from classmates and making social and networking connections? Perhaps private schools are expensive, but UC Berkeley, UIUC, UWashington, Georgia Tech are more affordable, especially with Pell grants etc. Especially part-time.
Also - people doing self-study tend to go right for the immediately useful stuff - how to make web pages in PHP and the like. How many people spend eight months studying calculus, then four months studying discrete math, then four months on graph theory, then four months on theory of computation, then four months studying logic gates and processors, then four months studying data structures etc.? What kind of code is someone who has not studied concurrent programming going to write when an application needs threading?
A degree is also a sign someone can stick with something for four years.
Of course a degree is no guarantee they know anything in and of itself.
Really? This has not been my experience at all. Nearly all tech job listings I've seen mention "or equivalent experience" somewhere.
How far back is this experience?
Is this what the job listings (of what there were) said during the 2008-2009 recession? Is this what they said in 2001 after the dot-com crash?
They may not say them now, they may not have said them in 1999, but they certainly are requirements companies can (and do) put up during the years when people need a job most.
* The Cell: A Molecular Approach, Cooper
* Molecular Biology of The Cell, Alberts
Theses are the main two books in the field of molecular biology. If you want to go more specific, let me know.
The courses at ADUni are really awesome. Though the resolution totally sucks and it feels rather old, they're the best thing around the Internet thats a tutorial on CS. They have everything from Algorithms and Discrete Maths to OOP and stuff. Check those out at http://www.aduni.org I'll probably send a pull request to whoever's maintaining the repo. Great job though, you've listed quite a lot of courses... ;)
Furthermore, the most theoretical course there is the Princeton one. The rest all focus more on using algorithms to do things than on theory.
Introduction to Cryptography:
Yehuda Lindell - http://u.cs.biu.ac.il/~lindell/89-656/main-89-656.html
Jonathan Katz - http://www.cs.umd.edu/~jkatz/complexity/f11/
Luca Trevisan - http://www.cs.berkeley.edu/~luca/cs278-08/
Yehuda Lindell - http://u.cs.biu.ac.il/~lindell/89-856/main-89-856.html
Jonathan Katz - http://www.cs.umd.edu/~jkatz/gradcrypto2/
Jonathan Katz - http://www.cs.umd.edu/~jkatz/gradcrypto2/f13/