How do I completely-self-study Computer Science? [closed]

Question

Being a completely self taught programmer, I would like it if I could better myself by self-learning the computer science course taught to a typical CS grad.

Finding different resources on internet has been easy, there is of course MIT open course ware, and there are Coursera courses from Stanford and other universities. There are numerous other open resources scattered around the Internet and some good books that are repeatedly recommended.

I have been learning a lot, but my study is heavily fragmented, which really bugs me. I would love If somewhere, I could find a path I should follow and a stack I should limit myself to, so that I can be sure about what essential parts of computer science I have studied, and then systematically approach those I haven't.

The problem with Wikipedia is it doesn't tell you what's essential but insists on being a complete reference.

MIT open course ware for Computer science and Electrical Engg. has a huge list of courses also not telling you what courses are essential and what optional as per person's interest/requirement. I found no mention of an order in which one should study different subjects.

What I would love is to create a list that I can follow, like this dummy one

SUBJECTS                                                        DONE

Introduction to Computer Science                                  *
Introduction to Algorithms                                        *
Discrete Mathematics                   
Adv. Discrete Mathematics
Data structures                                                   *
Adv. Algorithms
...

As you can clearly see, I have little idea of what specific subjects computer science consists of.

It would be hugely helpful, even if someone pointed out essential courses from MIT Course ware ( + essential subjects not present at MIT OCW) in a recommended order of study.

I'll list the Posts I already went through (and I didn't get what I was looking for there)

https://softwareengineering.stackexchange.com/questions/49557/computer-science-curriculum-for-non-cs-major - top answer says it isn't worth studying cse

https://softwareengineering.stackexchange.com/questions/110345/how-can-a-self-taught-programmer-learn-more-about-computer-science - points to MIT OCW

https://softwareengineering.stackexchange.com/questions/49167/studying-computer-science-what-am-i-getting-myself-into

https://softwareengineering.stackexchange.com/questions/19912/overview-of-computer-science-programming

Answer 1

I've seen some course material from MIT, and it was shockingly bad. They had teaching materials which required VC5, bunches of implicit global variables, passing colours as "Blue" instead of 32bit ARGB, let alone 4x [0,1] floats, that sort of thing. I wouldn't trust a curriculum or code just because it comes from a big-name university.

My CS degree (from a university which is top 10 in the UK for CS) consisted of:

First year:

1. OOP- the super basics
2. Computer Systems- stuff like, binary integer representations.
3. Basic relational database theory
4. Mathematics for CS- simple 2D and 3D geometry.
5. A little bit of HTML/JS- complete beginner's stuff
6. An equally tiny bit of PHP.
7. A tad of functional programming

Second year:

1. Legal issues in computing- stuff like, laws revolving around protection of user data
2. Programming languages- Chomsky hierarchy and lexing was covered
3. Operating Systems, Networks, and the Internet- mostly stuff like virtual memory and paging, IP stack
4. 2D computer graphics- mostly just proving theorems of the underlying mathematics
5. AI- basic descriptions of neural networks, Bayesian belief systems, etc.
6. Requirements analysis- brief overview of UML, functional/nonfunctional requirements.
7. Team project

Third year:

1. Algorithm analysis- complexity theory, mostly
2. Implementation of programming languages- LL/LR parsing techniques, CFGs, and such things.
3. Software Project Management- a look at Waterfall/Agile models
4. International Computing- Unicode and other localization fun
5. Advanced AI- don't know, honestly, and I've got an exam on it soon
6. 3D computer graphics- mostly, again, just proving theorems for rotation matrices and such
7. Agent-based Systems- mostly about asynchronous agents communicating, reaching group decisions, etc.
8. Microprocessor Applications- digital signal processing
9. Robotics- covers stuff like computer vision and robot decision making at a high level

As you'll notice, pretty much everything is "the basics" of something and almost nothing is covered to a useful depth.

The stuff that was actually worth doing, essential:

1. OOP- and then some more, and then some more
2. Functional programming- also some more. Try to pick a language like C++ or C# where you don't have to re-learn the syntax and tools, etc, to cover both styles.
3. The OS part- virtual memory is good to know about, as is kernel mode vs user mode. Skip segmentation and the IP stack.
4. Requirements analysis- Gotta be useful for any project
5. Algorithm analysis- knowing what algorithmic complexity is, how to reduce it, and what the complexity is of common operations is important.
6. Software project management models- many shops do Agile and many older ones still do Waterfall-style models.
7. International computing- Unicode is essential

The stuff that was worth doing, optionally:

1. Programming languages- Chomsky hierarchy, the tools of lexing and parsing. Skip the theory behind LL or LR parsers- an LR parser can accept virtually any realistic unambiguous CFG, and when it can't, your parser generator's documentation will tell you about it.
2. 3D Graphics. I don't mean "Prove this is a rotation matrix formula" wastes of time, I mean actual "This is a vertex shader" stuff, or GPGPU. That's fun, interesting, and different.
3. Some of the AI stuff is fun- like potential fields and pathfinding.

Stuff that's essential but I didn't cover it anyway:

1. Concurrency- a must-know, at least the basics, for anyone in 2012.

The rest were a complete waste of time. Unfortunately, most of these nine points I either already knew, or picked up the useful parts elsewhere. If you read about things like the FizzBuzz problem it rapidly becomes apparent that you don't actually need to know all that much to be on top of the pack- which is fortunate, since my degree and many of the materials I've seen online for other degrees really do not teach much at all.

Answer 2

Open Course ware is just a list of courses that they have made available. If you want to know what a student would have taken, swing by MIT's(non OCW) website and look at the actual program. They have a list of what is required and what is considered a prereq for what. Here is their page.

Answer 3

Try the 2001 Computer Science curriculum recommendations from ACM/IEEE, linked here: http://www.acm.org/education/curricula-recommendations

along with the 2008 CS updates.

Page 17 of the 2001 report has a handy chart which underlines all the "core" knowledge and still lists electives.

An undergraduate program wouldn't have time to cover even the courses considered core by these recommendations, so they will lump some of the categories together and let the students pick amongst them (eg, Operating Systems, Programming Languages, and Software Engineering get lumped into Software, and students pick a track).

You can find the required coursework on the CS department website for pretty much any school, and they should be some version of this.

Answer 4

If I may, I'd like to suggest joining github.com as part of your learning process.

Then you can search around for code that has some real world application that you're interested in, clone it for yourself, work with it, code on it, and get to know it, and eventually start to submit patches back to the source project, and down the line be working on an open source project that you have a vested interest in.

And, of course, you'll get familiar with git, which is just all the better.