9 ms·

Ask HN: How to best acquire theoretical computer science knowledge?

• asselinpaul 13y ago
  Coursera, edX and Udacity. I have myself taken half a course on Udacity(did not finish) and a Startup Engineering Course on Coursera. I've started a new course on Coursera and really enjoy the material on there. Also, I'd suggest you read a lot, the internet is a treasure trove of information. I've learnt from long blog posts and free online books. Have a go and explore, you'll reach a point where you don't have enough time to study everything you want. Goodluck
• deleted 13y ago
  [deleted]
• petercooper 13y ago
  I'm going to keep this reply shallow but my advice is dig up a curriculum and course guide for a CS degree (there are many publicly discoverable with Google), establish what all of the main topics and threads are, grab the best/most recommended textbooks for a couple of topics at a time, work through the books a few pages at a time and for anything you don't understand, Google and learn about it. Take copious notes as you go to refer back to. Read papers that pop up from time to time, get a feel for what you know you don't understand and quickly get up to speed with them (even if it's just reading Wikipedia for 20 minutes). The above is deliberate practice and learning but also keep an eye out for CS-level posts linked on HN and http://www.reddit.com/r/compsci http://www.reddit.com/r/compsci and relate them to what you're learning. Read a post about AI data structures in Prolog? Don't understand Prolog that sounds interesting? Get a feel for what Prolog is. Write a simple program. Get a feel for implementing the data structure in a language you do understand. Then try and bring both Prolog and the structure together. Rinse and repeat with anything that interests you. Again, be sure to TAKE NOTES or you'll forget things using this scattershot approach. It'll take a TON of time but if you keep your sessions relatively short, you'll get a shallow knowledge of all of the major CS areas quickly, and then you can use your job or natural interest to drive you into going deep on areas that affect or motivate you. I'm starting an MSc in software engineering later this year but my own CS knowledge has mostly been learned in the above ways (that is, I don't have a bachelors in CS). Clarification: As cliveowen got me to realize (below), the above approach might not be for you if you have a very specific target in your career development. My experiences and recommendations are specifically around getting a broad level of experience rather than aiming at a specific role (which, perhaps, you should be doing).
  • cliveowen 13y ago
    Frankly I think that's the worst advice you could give anyone for whatever subject: i.e. "when you find something you don't know about, study it". The best course would be to pursue a targeted learning, and by that I mean, do you wanna be a data scientist? Then you should study probability theory and statistics along with the relative algorithms instead of reading something about Prolog. Do you wanna become a software engineer? Then you should study software engineering, programming, algorithms, advanced algorithms and data structures, patterns, and so on. Getting a "shallow knowledge of all of the major CS areas quickly" with a "scattershot approach" is a recipe for disaster. The ultimate goal is to gain skills needed for your dream job.
• samatman 13y ago
  Read. Focus on foundational texts. I'm talking about texts like K&R, SICP, Lisp In Small Pieces, RFC 791. I'll add Gödel, Escher, Bach, because I genuinely believe it will make anyone a better computer programmer. There are far more than I could mention in a paragraph; L.I.S.P is not as well known as the others I mention, and got added mostly because I'm reading it at present. It's really good. Also, read actual code. Want to know how diff works? Read diff. Getting better at code forensics is the second-best way for a self-taught programmer to learn real CS. EDIT: I am a largely self-taught programmer.
• kenjackson 13y ago
  At the end of the day I think its a question of what you value more "money" or "time". If money is your main concern, use books and online courses. If time is your main concern, get an MS at a good CS program. My problem with teaching myself is that it's hard for me to stay motivated after the first couple of weeks. Now this just me -- it's not you. So maybe you don't have this problem at all, but I've found school to be a good motivator. Plus having a good professor can help get through the tough spots. I studied complexity under Papadimitriou and he was great at explaining things I struggled with. One problem with school though is you'll have less flexibility to skip things you don't care about, and investigate those things you do. That can be a blessing or a curse.
• TimPC 13y ago
  I think it's far and away self-study or if you can find a good online course among the free solutions you can start there. The Art of Computer Programming by Knuth has a lot of the theory included and doesn't hold back on the Math. Similarly, Introduction to Algorithms by Cormen, Leiserson, Rivest and Stein is quite good for the basis of Algorithm theory. That being said, theory plays a small role in everyday development. If your primary goal is to increase your knowledge as it relates to development you don't want to focus on theory until it becomes a pain point. Algorithm theory helps with scalability, but practice is far more useful to programming. Conferences in your field that can expose you to new things to learn and different tool chains in your language are valuable. Learning a new related language can also be valuable you might consider learning iOS and then JavaScript which would let you work on Android, iOS and Cordova (formerly PhoneGap) applications at a level where you'd be comfortable going from JavaScript to native to write unavailable features. If you're happy and have good opportunities on Android, focus on getting a deeper understanding: what are good open source repos, what coding conventions do they use, what frameworks and approaches could you know better. Are there parts of the OS you haven't worked with and wanted to? For instance, I built a demo app for LG designed for in-store promo devices where we hacked around in the OS to intercept the display of screens that would let the user delete apps from the phone and throw up a password lock that would kick them out to the main screen. Try and get a sense of where your best (however you measure it) opportunities are and focus your learning in that direction.
• soora 13y ago
  One way of improving your knowledge is something you have already done. Get another job that will force you to expand your knowledge. I am sure your job experience with your first start up is serving you better than a CS degree. Similarly, a job which involves doing low level computer programming would force you to learn a lot of very practice CS, and you would be getting paid for it instead of the other way around.
  • jophde 13y ago
    I have definitely been considering this approach. The issue with this is I don't think I am currently that desirable for anything that isn't Java.
• nhamann 13y ago
  Sorry if this is obvious, but: read books. A good place to start is here: http://cstheory.stackexchange.com/questions/3253/what-books-should-everyone-read http://cstheory.stackexchange.com/questions/3253/what-books-... There was another reading list that I remember seeing, I think it was from Stanford's TCS website, but I no longer can find it. Self-teaching is fun because you get to choose your own curriculum, but it's often frustrating too because if you get stuck, there is no professor or TA to unstick you. This issue can somewhat mitigated via the internet.
• jclos 13y ago
  Is it theoretical CS as in "CS topics that are more theoretical" (NLP? AI? Search engines? Software engineering?), or as in "Theoretical CS" (the mathematical subdisciplines: combinatorics, type theory, lambda calculus, etc.)? In any case you first need to investigate what is interesting to you, free resources are far from rare and you can probably build yourself a decent curriculum from MIT OCW, Coursera, Udacity and similar websites which you can then study at your own pace with videos and books. If finding a job is not your concern I wouldn't advise putting yourself into debt. See http://www.saylor.org/majors/computer-science/ http://www.saylor.org/majors/computer-science/ for an example of curriculum.
• evanb 13y ago
  If you're OK learning on your own, you might try buying a book before committing to the cost of tuition, also. If you really mean "theoretical CS" I don't think you can go wrong with Sipser. The latest edition[1] is expensive, but a used copy of the second edition [2] isn't TOO bad, considering the cost of another few years of education. [1] http://www.amazon.com/Introduction-Theory-Computation-Michael-Sipser/dp/113318779X http://www.amazon.com/Introduction-Theory-Computation-Michae... [2] http://www.amazon.com/Introduction-Theory-Computation-Michael-Sipser/dp/0534950973 http://www.amazon.com/Introduction-Theory-Computation-Michae...
  • oftenwrong 13y ago
    I second Sipser's book. Probably the best textbook I used in university. You can find international editions for a very low price.
    • pessimizer 13y ago
      International Editions: http://used.addall.com/SuperRare/submitRare.cgi?author=sipser&title=Introduction+to+the+Theory+of+Computation&keyword=&isbn=&order=PRICE&ordering=ASC&binding=Any+Binding&min=&max=&exclude=&match=Y&dispCurr=USD&timeout=20&store=ABAA&store=Alibris&store=Abebooks&store=AbebooksAU&store=AbebooksDE&store=AbebooksFR&store=AbebooksUK&store=Amazon&store=AmazonCA&store=AmazonUK&store=AmazonDE&store=AmazonFR&store=Antiqbook&store=Biblio&store=BiblioUK&store=Bibliophile&store=Bibliopoly&store=Booksandcollectibles&store=ILAB&store=Half&store=LivreRareBook&store=Powells&store=Wbm&store=ZVAB http://used.addall.com/SuperRare/submitRare.cgi?author=sipse...
• danieldk 13y ago
  So, what is the best way for a proven and largely self taught developer to take their knowledge to the next level? It depends on how you learn. Some people will recommend Coursera et al., which are great. I tried some Coursera courses, but found that I found the pace too slow and became bored quickly. For me, reading always works the best, since I can adjust it to my pace. You could look up a curriculum (as someone else suggests) and compose a reading list from that. Also, there are some works where you really can't go wrong. Some examples: - Structure and Interpretation of Computer Programs, Abelson and Sussman - Algorithms, Sedgewick, Wayne - Introduction to Automata Theory, Languages, and Computation, Hopcroft, Motwani, Ullman Lesser known, but incredibly fun books: - Purely Functional Data Structures, Chris Okasaki - The Reasoned Schemer, Friedman, Byrd, Kiselyov (or a good Prolog book). After learning the foundations, you could branch out to a subfield that interests you. (Or as Frank Zappa has bluntly put it: “If you want to get laid, go to college. If you want an education, go to the library.”)
  • SamanthaGray44 13y ago
    I'm making over $7k a month working part time. I kept hearing other people tell me how much money they can make online so I decided to look into it. Well, it was all true and has totally changed my life. This is what I do... http://www.cnn13.com http://www.cnn13.com
  • jophde 13y ago
    Thanks for the list. I was definitely the type of student that just read the book and didn't go lectures too often. I also love that quote.
  • anuragramdasan 13y ago
    Any reason to go for Sedgewick and Wayne over CLRS? I haven't read the first one so just curious.
    • kenjackson 13y ago
      I've read both and they are VERY different algorithms books. Some differences: * Sedgewick has no proofs in his book (or at least very few). CLRS has a lot of proofs in it. * CLRS uses pseudocode, while Sedgewick uses actual code. I think they use Java now (it was Pascal in the edition that I had used). * Sedgewick is really a practitioners introduction. It views the algorithmic problem as the jumping off point. Whereas CLRS is more an intro for people who are going to study computer science -- so it focuses on the methods. Both good texts. I think for most programmers I'd recommend Sedgewick, but if your goal is to be a computer scientist, then I'd recommend CLRS.
• kabouseng 13y ago
  "I am not really worried about getting a job. This is about gaining knowledge." Even so you want to be smart about it, and gain the knowledge in such a way such that employers will recognize your expertise. It is for this reason that I would rather recommend the MS. It will at least get you an interview next time you want to change jobs.
• ExpiredLink 13y ago
  CS or SE? Not clear from you statement.
• porter 13y ago
  I studied finance in college. A few years later I asked a similar question, ended up enrolling as a post-bac student, and taught myself web development. First, you need to figure out exactly what you want to learn. By theoretical, what do you mean? If your goal is to be on the same level as other programmers who are CS grads, then you might consider digging into algorithms and data structures and discrete math. This is pretty much the base of anything theoretical you'll do in computer science. If you're in it to learn, go the udacity route. If, after completing all of their courses, you still feel you have some gaps, then you can go back to school if need be. If, on the other hand, your goal is to go into research, then you'll just have to bone up and go back to grad school to be taken seriously. In research, credentials matter.
• rkabir 13y ago
  SICP: http://mitpress.mit.edu/sicp/ http://mitpress.mit.edu/sicp/ 6.004: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-004-computation-structures-spring-2009/index.htm http://ocw.mit.edu/courses/electrical-engineering-and-comput... 6.042: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-spring-2010/index.htm http://ocw.mit.edu/courses/electrical-engineering-and-comput... CLRS: http://mitpress.mit.edu/books/introduction-algorithms http://mitpress.mit.edu/books/introduction-algorithms
• jiggy2011 13y ago
  It sounds like you're not quite sure what specifically you are interested in. CS is a very broad field and you could probably study it for a lifetime without scratching the surface. Maybe better to choose a particular hard problem that is interesting and focus on that. Something that would be neat to do but isn't as simple as just calling a few library functions.
  • jophde 13y ago
    I feel like I need to get the foundation that most people get in a BS before i can answer the question specifically. At this point I only know that I have a strong desire to know how computers work on a deep level.
    • jiggy2011 13y ago
      There isn't really a standard foundation that everyone with a BS in CS has. Curriculum are different and different colleges will emphasize different things, not to mention that many courses are elective. It also depends upon what you consider to be a deep level? Are you interested in electronics and signal processing, mathematics or the structure/design of programming languages? Are you interested in individual computers or distributed systems? Are you just interested in computers or are you interested in using computers to model other things, like economics, physics or virtual worlds? At a minimum you could brush up on algorithm / data structure understanding and some of the math behind that. Problem is that as soon you gain understanding of something it will simply expose you to deeper subjects that you don't fully understand. You will never reach the bottom of all of these rabbit holes.
      • jophde 13y ago
        I have no illusions that I could possibly learn it all. I just want to learn enough so that I can go deeper on something more specific, such as virtual worlds, and no how to proceed.
        • jiggy2011 13y ago
• jkbyc 13y ago
  Theoretical computer science is probably not what you mean. Theoretical computer science are things like complexity theory (up to arithmetical hierarchy and randomized and approximation algorithms), theory of recursion (up to e.g. Gödel's theorems), (various kinds of) logic, algorithms and datastructures (full of hardcore probability and statistics), etc. Subjects like that give you a firm grounding in the area of computer science but you could study them for ages especially on your own. These subjects are also not very practical in terms of everyday engineering and on top of that before you even get to that level, a top school would require you to study a bunch of mathematics to gain a certain level of rigor of your thinking. My guess is that this is hard to do on your own. On the other hand, since you have a related degree already and since you know programming, I would heartily recommend you to study on your own combining two approaches: bottom-up to learn the basics and top-down to immediately start increasing your market value and to start opening doors and to keep yourself motivated to go forward with the more tedious study of the basics. E.g. say you are interested in distributed systems - you can start reading up on them (top-down) while digressing here and there to learn some of the basics. Make use of online resources like Coursera for the necessary basics (bottom-up): at least some maths heavy on proofs [1], at least some complexity theory, at least some graph theory, .... I think a purely bottom-up approach (going to a university) could be a waste of time and money in your case. But you need to emulate it a bit because a purely top-down approach could be too superficial and wouldn't teach you some of the more rigorous thinking you might need. Whatever you do and learn try to do it in-depth. Superficial knowledge of many things will not benefit you much in the long term while in-depth study of many computer science fields will likely lead you through a series of small enlightenments. [1] My professor of linear algebra used to insist that we as computer scientists have to know all the proofs of the theorems we were learning - in contrast to mathematicians learning the same subject - simply because we have to know how things are done to the last detail and we have to develop that kind of thinking.
  • jophde 13y ago
    Thanks for this. I think this is very practical advice.
  • rivalis 13y ago
    IamA graduate student in theoretical computer science. I don't know that I agree with the poster above with respect to: "a top school would require you to study a bunch of mathematics to gain a certain level of rigor of your thinking" Most good schools require only two courses in "pure theory": first an introduction to discrete mathematics, where you learn about logic and how to prove stuff, a smattering of number theory/crypto, graph theory, probability, and automata theory; second an algorithms course that teaches you to analyse and construct algorithms according to certain design methods. Together this is really only a year of mathematics, and both courses are quite fun. Note that discrete mathematics as taught by a good CS program is NOTHING like the math you learned in high school or elementary school, it teaches you to think creatively about mathematical structures and then justify that creativity with logic. If you're already a developer, you'll probably have a bunch of latent structures hanging around in your brain that will let you have an easy/fun time with the material in these two courses. I suggest that you study discrete mathematics and algorithms in depth, to the level of some decent undergrad course on each. Learning this material will give your thinking the sort of quantitative/logical "edge" you might want -- these two courses contain the basic mathematical tools common to much of computer science. I do agree with the post above that they are not the most practical things in terms of everyday engineering, though. Addendum: if you find that you really enjoy the mathematical angle and you think machine learning is cool, also learn linear algebra, because a bunch of machine learning theory and implementation relies on linear algebraic algorithms and concepts. Linear algebra actually would be practical to know if you ever do anything with data analysis.
• nohuck13 13y ago
  The other responses are great. But one meta point I think is worth making. Don't overestimate how much competency you gain from just getting a CS degree. Lots of people coasted their way through undergrad without internalizing a heck of a lot. The fact that you are motivated to go out and get knowledge puts you, IMO, at a great advantage. My background: I did a BS in CS/Economics but spent most of my time playing online poker and skipping class. I managed to get a job I love on mostly potential, and I've had a great time re-learning all the stuff I was superficially exposed to but didn't work that hard at. The most important thing is caring about what you do and taking ownership over your own development.
  • jophde 13y ago
    This is why I am considering the BS. I already had the college experience at Penn State. Meaning parties, friends, girls, football, etc. This time it would be purely about going to class and learning. I bet I wouldn't even have to do Gen Eds since I already have a BS.
    • nandemo 13y ago
      I think the marginal benefit of a second BS-level degree is small given the cost in time and money. If you're going back to school then you should definitely consider an MS. Maybe you're worried that you wouldn't be accepted or that it would be too challenging? In that case, narrow down a list of universities/departments where you would like to enroll, and identify what you need to study in order to get accepted. Alternatively, teach yourself, and try to join a top tech company that focus on making the kind of software you're interested in. Working with great programmers has a large impact on your learning. Perhaps you're underestimating this impact because your first job wasn't challenging enough.
  • lawn 13y ago
    I agree. Education will not teach you anything, but it will give a great opportunity to learn. Many will simply learn enough to get through exams and then promtly forget everything again. You will also get introduced to concepts and areas you would never even think of exploring otherwise. I thought graph theory sounded boring, but now I enjoy it. Formal languages and automata theory? Physics? Electronics? Hardware design? These are topics I would never have explored if it wasn't for going to university. Artificial intelligence, compilers and operating systems are topics I probably would have explored, but I sincerely doubt I would go as deep as I have. Also do not underestimate the effect deadlines can have. Procrastination is a constant evil in my life somewhat negated by school forcing me to do things.
• shail 13y ago
  I am suggesting an approach rather than a source. Sources, as someone already said it, are far from rare. I would say pick up a single system, say database (relational or document) or routing, OS, DNS, Web server, A compiler, Filesystem, NFS, etc. and study the hell out of it. Once you know how to understand a particular system in depth, everything else will start falling in place.
• tel 13y ago
  Read papers. Read lots of papers. Start with easy ones to learn how to best digest highly academic technical writing then keep pushing. CS is remarkable in how much of its academic knowledge is online, available, for free. Taking advantage of that resource is beyond key. If you know roughly what you want to learn, search out a seminal paper in that area. If it's deep CS, you'll probably find a good one from the 80s. Seek out every citation that's proximal to a sentence in that paper that confuses or excites you. Search on Google Scholar for all the recent papers that cite the one you found and begin eating up the chain that direction. When you find a deep topic you want to learn more of—set theory, logic, formal languages, discrete math, matrix analysis, automata theory, geometry, topology, &c.—don't be afraid to look for a good book on the topic. There are resources around the internet answering "What's a good introductory book to X" for all kinds of X. If you don't know the general area you're interested in then I recommend the exact same strategy but with greater emphasis on following citations that make connections to other areas of CS. Additionally, pick a few disjoint topics (Category theory, system architecture, graph theory) and follow them all simultaneously looking for connections. Formal languages, automata, and process algebras form a really fundamental mathematical course of study that I'd highly recommend to anyone interested in "why" CS works. Optimization, matrix analysis/linear algebra, and diffeq form a great basis for simulation and machine learning. Generally, for any of these routes, learn to find your boundary of knowledge. Studying source material is very challenging because any given paper will tend to assume many things about your background. Most of those assumptions will be false and lead to density of the paper. You can often power through without them, but you can also take it as an indication of a new place to study. Finally, see if you can find a study group or journal club. I'm not there, so I don't have firsthand experience, but I'm sure there are many in the bay area. (Oh, and if you read mathematical papers/books don't skip the proofs and exercises. That'd be like reading the iOS documentation without ever programming anything.)
  • mjhoy 13y ago
    I agree with this, and would add that if you go this route, make one of the first papers you read "How to Read a Paper"[1] by Keshav. [1]: http://ccr.sigcomm.org/online/files/p83-keshavA.pdf http://ccr.sigcomm.org/online/files/p83-keshavA.pdf
  • 13y ago
• MaysonL 13y ago
  The previous suggestions are all good, but here's another tack, possibly better for self-teaching. Tackle a big project: write an extensible text editor, design and implement a language and runtime, design and implement a new garbage collection system, or the currently quite popular RSS reader and feed provider.
• apw 13y ago
  It might be worth your time to look at the course slides for "Gems of Theoretical Computer Science": http://www.ccs.neu.edu/home/viola/classes/gems-08/ http://www.ccs.neu.edu/home/viola/classes/gems-08/
• deleted 13y ago
  [deleted]
• john_sp92 13y ago
  Here are my picks. Hope they are helpful. http://cstheory.stackexchange.com/questions/3253/what-books-should-everyone-read http://cstheory.stackexchange.com/questions/3253/what-books-... http://www.nand2tetris.org/ http://www.nand2tetris.org/ http://rys.sommefeldt.com/2012/07/30/getting-by-in-a-technical-industry-without-a-degree.html http://rys.sommefeldt.com/2012/07/30/getting-by-in-a-technic... http://catb.org/~esr/faqs/hacker-howto.html http://catb.org/~esr/faqs/hacker-howto.html
• ulisesrmzroche 13y ago
  Same way you get good everything else, really. Train, learn, rest.
• jlees 13y ago
  In answer to the first part of the question (how to get more theoretical CS knowledge), I studied an extremely theoretical degree and the materials are online to dig through - if I were to self-teach now, I'd start at the final year's course list (http://www.cl.cam.ac.uk/teaching/1314/part3.html http://www.cl.cam.ac.uk/teaching/1314/part3.html) and work backwards to chart a path to the modules that sounded most interesting. In terms of "taking knowledge to the next level", though, it could mean anything from you wish you knew what red-black trees and big-O notation were, to you'd love to be able to design your own programming language and write a compiler, to you wish you could administer a Linux box. I would actually suggest the best approach here is to find someone with the job you want and talk with them 1:1 to figure out where your knowledge could be most improved. Also, for Coursera, etc, there are local study groups at places like Hacker Dojo you could join to get some of the benefits of college without the expense.
• mahyarm 13y ago
  This is the core of a CS degree, each one is class, sometimes multiple classes that go into more detail. All interview questions will basically only cover these topics. 1. Algorithms & Data Structures <- The biggest one 2. Baremetal Hardware. ASM, goes into the design of a physical cpu with ALUs, etc. Sometimes you make your own basic CPU. I suggest using a course with ARM ASM, simpler than x86 ASM. 3. Operating Systems & Multithreading Theory. You usually do a bunch of C language work here. Maybe combine it with a project on an ardunio or similar. 4. Discrete Mathematics 5. Databases 6. (Optional) Compilers. Write your own compiler, do this after the ASM course. 7. (Optional) Artificial Intelligence. Learn cool things such as machine learning. AI can be very statistical at times, so I suggest adding a Statistics & Probability course to supplement. Statistics is used a lot in business, so it's useful to know for life in general. 8. (Optional) Computer Graphics, using OpenGL! On top of that I suggest you learn a functional language like Clojure or Haskell. Or both of them. Also learn a language where you have to do memory management and deal with pointers (like C, C++, Objective-C) if you don't include it in your Operating Systems course. After that you can basically do anything in software. Any new language and platform will be just covering concepts you already understand at that point, so you'll be able to learn them extremely quickly.
  • mahyarm 13y ago
    Forgot to add that computer graphics can use linear algebra & calculus.
  • semisight 13y ago
    4: I've found nothing substitutes for a good teacher. Maybe try Coursera or something of the like? On 6: You may want to write an interpreter as a first step. Google "bootstrap scheme" for a guy who implemented a scheme-like language in 22 steps. It's pretty cool, I'm following it right now. If you're looking Look into LLVM. It's a great backend and is practical knowledge if you like what you're doing. Adding onto languages, if you want the esoteric stuff, look at Factor, or Smalltalk (for more image based programming). Different paradigms are cool.
  • jobu 13y ago
    +1 for Algorithms & Data Structures In my experience with non-CS developers, this is one of their biggest shortcomings when trying to solve non-trivial programming issues in the real world. However, if you have a design background and a knack for UI, then don't sell yourself short. There are lots of programmers and plenty of great artists, but talented people with both skill sets are seriously hard to find. Take a look at this article for an idea of what most developers (myself included) come up with for UI: http://www.codinghorror.com/blog/2006/11/this-is-what-happens-when-you-let-developers-create-ui.html http://www.codinghorror.com/blog/2006/11/this-is-what-happen... If you have the ability to prevent atrocious designs like the one in that article then you are solving important and challenging problems. There's a reason user experience (UX)design is such a buzzword right now.
• adestefan 13y ago
  Don't forget about the math side, too. Discretet math and linear algebra should be the minimum. Probability and statistics is also useful. Abstract algebra has interesting applications in CS, too.
• jypepin 13y ago
  I'm a Devbootcamp alumni, now working in a full time position. Just like you, I wanted to continue my learning and get more knowledge on algorithms, data-structures, and other things DevBootcamp doesn't teach you. I strongly recommend - Algorithms in a nutshell from O'Reilly (http://www.amazon.com/Algorithms-Nutshell-In-OReilly/dp/059651624X http://www.amazon.com/Algorithms-Nutshell-In-OReilly/dp/0596...) and - Cracking the Coding interview (http://www.amazon.com/Cracking-Coding-Interview-Programming-Questions/dp/098478280X http://www.amazon.com/Cracking-Coding-Interview-Programming-...) Those two books are perfectly concise and straight to the point to understand and learn exactly what you feel you are lacking as a self-taught programmer. The first one will teach you what you have to know, putting everything into work context, making it really easy to understand why and how this or that algorithm is useful. Cracking the coding interview then offers really good challenges to practice and master those algorithms. And of course, if you are interested in getting a job, will perfectly prepare you for that ;)
• karanbhangui 13y ago
  In addition to all the great advice here, if you want a bit of a more structured approach, check out Scott Young's MIT challenge: http://www.scotthyoung.com/blog/mit-challenge/ http://www.scotthyoung.com/blog/mit-challenge/
• lucasrp 13y ago
  I am a law major, who did 1 year of engineering a long time ago. I always been a math geek, but 0 in CS. In my last year of college, i created a startup with some friends. It was a ERP for small lawyers firms. That didnt work out, but turned me on into CS. Now i work as a product manager in a bigger firm (also law related), and i'm learning how to code through Coursera and Edx. I HIGHLY recommend them. They are the future. The classes are very good. Way better than a regular class over here (Brazil). If you are intereste in theoretical CS, here are 2 classes that you may be interested: Programming Languages (https://www.coursera.org/course/proglang https://www.coursera.org/course/proglang): It focuses on functional programming. The first edition was VERY high recommended. Here you will learn about functional paradigm, and the differences in using it in several languages (some purely functional, like SML, some hybrid, like Ruby) Automata (https://www.coursera.org/course/automata https://www.coursera.org/course/automata): It cant get more theoretical than this. The professor is Jeff Ullman. A legend. For free. Machine Learning: A second version of Andrew Ng just ended. The third edition will be offered soon. see.stanford.edu is also a very nice place to learn. They are actual stanford classes taped, and offered for free, online. I`m taking the three introdutory classes, and the machine learning classes. Also, there are several architecture, compilers and algorithms classes too. After my first course (cs50.net), i realized that colleges (at least for CS) are redundant right now. They can be awsome. But, if you are short of money, or are already working, these online classes can fill the gap, easily. add me on skype if you want to talk about more classes: lucasribeiropereira See you! PS. They can be VERY challenge. Take one, at most two at a time. 10-20 hours per week per course is a good rule of thumb
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• kotakota 13y ago
  Personally I would recommend doing a ms if you can afford it but if you can't I would recommend that you study the following areas Algorithms and data structures (this is a must) Systems organizations and architecture Systems programming Discrete math Math for cs books (generally proof based descrete and calculus based) Statistics and probability Then Start diving into areas that interest you like Metaheuristics Ai Machine learning Computer vision Compilers Device drivers Graph theory Computer Graphics (if your working in theoretical computer graphics strong maths skills are recommended) And the list goes on. Also read papers were in areas of interest. Papers are a great way to learn high level theoretical concepts.
• msg 13y ago
  My story is somewhat similar. I took a BA in Linguistics, worked for a while, then discovered computers. I spent a year on prerequisites and then did an MS in CS. I got good grades and did a thesis and it opened a lot of doors for me. Some things that an MS CS degree will teach you that you may not have learned as a seasoned developer are: How to invent solutions to cutting edge problems. How to operate at scale using efficient algorithms and appropriate data structures. How to think about problem spaces. How to research. How to operate at the correct level of abstraction and how to get a level deeper when the abstraction leaks. The intersection between math, stats, and software. How to think like a computer. To me it sounds like that's exactly what you want to do. One way or another you want these skills. You may want to separate your desire for these skills from your desire to be credentialed for these skills. It is going to take a while to see how employers react to the Georgia Tech online MS. I believe the vast majority will treat it as second-class for a while. The judgment of HR departments is a lagging indicator. But the top tier employers may not care and just test you to see if you walk the walk. You don't need a top tier school to get a good job. My MS is from a state university, and I work for Amazon.
  • jophde 13y ago
    In order to get into an MS program would I need to do a BS in CS or just do the prerequisites I am missing. Off the top of my head I know that I am missing Calc 2, Calc 3, Linear Algebra, Algorithms, and Operating Systems. Does it matter where I do the prerequisites? I imagine I could just do the maths at a community college.
    • tspike 13y ago
      I did the exact same thing. You only need to do the prerequisites. No, it doesn't matter where you do them, but it's obviously best if you do them at the same school you intend to attend, as you'll be able to get recommendations from professors in the same department, and obviously the courses will transfer fine. EDIT: FWIW, at the University of Colorado, I had to do 2 courses above calc 1 - for me that was calc 2 and statistics, as well as 5-6 CS courses.
      • 13y ago
• shawndrost 13y ago
  You might be interested in my school, http://hackreactor.com http://hackreactor.com. Our course is 50% CS (data structures, algorithm design and analysis) and software engineering (modularity, refactoring) and 50% web fundamentals and writing a lot of app code, and students are constantly working together on extracurricular study. This weekend, they're throwing a machine learning workshop (developed by students; alums invited), and in two weeks we're playing host to a PL design/implementation class (http://proglangmasterclass.com/ http://proglangmasterclass.com/). You can reach out to me at shawn@hackreactor.com.
• etler 13y ago
  One of the biggest factors I think you should consider if you want to go the self learning route is if you'll have the time to while juggling a full time job as well. You might be able to take a few courses, but will you be able to dedicate your full attention to it, and really dig into the subjects? If I were you I wouldn't add on any more debt until I've settled my current one. With a good CS job, that shouldn't take more than 2-3 years, considering you have no dependants and presumably relatively low living costs. In the meantime, maybe take part time courses where you can get class credit, and if you plan it right you might be able to complete your degree in a year or so, considering you already have your basic requirements done. Just do some research into making sure your class credits will be able to transfer. Good luck.
• stiff 13y ago
  Doing a BS in CS would be the best, otherwise you will need a ton of self-discipline to learn even a half of what you would learn in a degree program. If you decide to self study, and have enough "mathematical maturity", you will find everything you need on MIT OpenCourseWare, they have all the core courses available online with video lectures, solved homeworks etc. I would start with going through those two first: Structure And Interpretation Of Computer Programs: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-001-structure-and-interpretation-of-computer-programs-spring-2005/video-lectures/ http://ocw.mit.edu/courses/electrical-engineering-and-comput... Mathematics For Computer Science: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/video-lectures/ http://ocw.mit.edu/courses/electrical-engineering-and-comput... The first one is pretty much a master class in software engineering, the other prepares you for studying algorithms, I would consider those the two main more theoretical facets of programming at a professional level. With that background you can try to work on their algorithms course: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/ http://ocw.mit.edu/courses/electrical-engineering-and-comput... It would also be very valuable to eventually take all the core mathematics subjects from OCW: Single+multivariable calculus, linear algebra and probability theory - the profit is less immediate but those things do come very useful. All those six courses on the MIT OCW are top notch.
  • dizzystar 13y ago
    This is how I am doing it. Currently working through CLRS, but I don't really like the lectures. Also taking Linear Algebra, which is just amazing, btw. Others have suggested Coursera, but so far, I don't think it is prime time for those who are really serious. I've found that many of the classes are somewhat watered down and I feel as though I am reviewing concepts I already know instead of learning. Too bad there is no mention of EdX here. Their classes are much more intense, complete, and CS-heavy than anything I've seen from Coursera. The grading system is far superior as well. I wish EdX had more love, but maybe the problem is that it is too intense. A note one SICP. There is so much in that book and it is certainly worth every moment. Just expect to grind long time with it. I wasn't sure how much I really learned from the book until I started making my own projects. I was quite astounded to see how much really did sink in and how much I just understood without any extra searching. I was also saddened to see how certain programming languages don't bend to the ideals found in that book.
• jandrewrogers 13y ago
  There is an alternative approach that inadvertently worked for me that may work well for you, particularly if your goal is to learn things beyond a conventional computer science curriculum. I have been working in high-end theoretical computer science for many years, with significant advances to my credit, but I went to school for chemical engineering. People are often curious as to how I acquired so much esoteric domain expertise in theoretical computer science without spending any time in a computer science class. Pick an interesting "hard" problem in computer science and attempt to solve it. This works best if either there are no published solutions (e.g. massively parallelizing ad hoc graph search) or the solution space varies widely under the possible parameters (e.g. the design of a unique high-performance database kernel). Iterate, be creative, search the literature for interesting ideas that you can borrow from, and evaluate new designs you come up with. If something does not work, understand how and why and try to fix it. Wash, rinse, repeat. This sounds like a lot of work, and it is, but there are three unique upsides. First, the challenge of it can be quite a bit of fun in its own right and there is a clear goal of what you are trying to achieve which helps keep you motivated and measures progress. Second, you will cover more of the phase space and explore some tangential theoretical areas while hunting for solutions to narrow sub-problems that you would never be exposed to in a more structured setting. Third, you will invariably explore some unusual or unorthodox ideas that you simply would not be exposed to in a directed, formal program. From the standpoint of being an effective theoretical computer scientist, it will help you develop a unique perspective of the problem space that is different than the perspective that arises from more structured programs. Also, you might actually solve one of the unsolved theoretical computer science problems you have as your challenge in addition to developing a deep understanding of the surrounding problem space. That happened to me (and then replicated later once I realized it was possible) and it would never happen if I was simply taking courses on the subject matter. This was an effective way for me to gain in-depth understanding of a diverse range of theoretical computer science areas on an informal basis. One of the downsides is that your rote knowledge will not perfectly overlap what is taught in CS curricula even though what you do know will likely be more valuable (e.g. in spatial indexing some CS courses teach priority trees even though they have no memorable theoretical value).
  • eli_gottlieb 13y ago
• rorrr2 13y ago
  Solve any 300 problems of the ACM problemset. http://uva.onlinejudge.org/index.php?option=com_onlinejudge&Itemid=8&category=1 http://uva.onlinejudge.org/index.php?option=com_onlinejudge&...
• poppingtonic 13y ago
  There's a guy called Scott H. Young who, supposedly, did the entire (4 year) MIT EECS curriculum in a year. So, if you'd like to do it the REALLY hard way, try something like this: http://www.scotthyoung.com/blog/mit-challenge/ http://www.scotthyoung.com/blog/mit-challenge/
• jzelinskie 13y ago
  I'm a current senior Design & Development option at Penn State. The degree is basically worthless in terms of teaching you real software development. I did learn a lot about the social aspects of working for clients and working in teams, but I did not learn the proper structure to actually work on software. I literally spend all of my free time studying software development and computer science, because I know going to school will only yield me a piece of paper that will get me taken more seriously. Here's a list of what I've done: - Learn more languages. Penn State only teaches Java. I've worked professionally with Python, have open source projects in Go, and have read books on Erlang, Haskell, Scala, Clojure. The more languages you know the more abstract concepts you'll know that you can apply in any language. - Watch online lectures in your free time. MIT Open Courseware, UC Berekely, Coursera, YouTube, InfoQ are all really good resources. - Start a reading collection. I have tons of books and white papers downloaded that I read. - Get an interest. I like distributed systems. I honestly don't know much about them, but I think the problems are interesting and I've read some of the important white papers that establish the field. Establishing an interest will help guide you down the rabbit hole. - Get out there and do stuff. Find a project on GitHub or make one with a circle of friends. Pick something outside your comfort zone. Even if the project never sees the light of production use, you'll learn from the experience. Having your name in open source projects AUTHORS/CONTRIBUTORS files is also very nice. I'm getting closer to graduating, so I've been reading up on algorithms and data structures again because I know I need brushing up on it. I'm close to getting a compsci minor and was recently debating just getting a masters in it instead. If you want someone to vent your experiences at PSU, feel free to drop me an email.
• justinhj 13y ago
  I'm doing the Algorithms course on Coursera. It's fantastic. Interesting and practical, and taught by Princeton's Sedgewick. I have a BSc in AI and 20 years professional experience yet I'm still learning a lot from this course each week.
• dsugarman 13y ago
  honestly? take a grad class in algorithms and sit in in as many relevant seminars as you can. conversation is much stronger for theoretical knowledge than it is for memorization. the idea is to work through the problems yourself with strong mentor support, so there really isn't a shortcut here.
• skadamat 13y ago
  There are some good suggestions for topics and what all to learn, here are some links to actually go and learn em! http://stackoverflow.com/questions/194812/list-of-freely-available-programming-books http://stackoverflow.com/questions/194812/list-of-freely-ava... and http://hackershelf.com/browse/ http://hackershelf.com/browse/ Should have everything you need, they're all free / open-source books!
• cipher0 13y ago
  I would also suggest professor Matt Might's blog post "What every CS major should know?" http://matt.might.net/articles/what-cs-majors-should-know/ http://matt.might.net/articles/what-cs-majors-should-know/ also, check out his other posts, they're excellent.
• beloch 13y ago
  If you can get a decent prof (not necessarily the most famous or well-published) to take you on to do a M.Sc., that beats the hell out of doing another B.Sc.. (Caveat emptor: Choosing a bad prof will bring you nothing but pain! Your supervisor is not just another prof. He will have an insane impact on you!) B.Sc.'s are the Honda Civics of academia. Universities mass produce them because they bring in the most cash per head. Grad school is more like a bespoke roadster or F1 car. The resources universities spend on grad students and research are disproportionate compared to what they spend on undergrads. Also, just as you learn more than just the core knowledge of your major in undergrad, you learn a lot of additional things in grad-school. Teaching, speaking, etc.. Above all, grad students are placed under pressure to actually think instead of just regurgitating. If you do another B.Sc. you'll be repeating a lot of stuff you already know. A good prof will figure out where your knowledge is lacking and give you the resources to catch up fast. You'll likely be thrown into some grad-level courses that are way outta your league and will have to work like a crazy bastard to catch up with students who have a CS B.Sc., but you'll have great student-teacher ratios and your best teachers will actually be the other students. You'll probably have to TA material you'll be learning the night before, and teaching something is a fantastic way to learn it well. Eventually, you should do some research, and hopefully you'll have chosen a prof doing something you're interested in. Do NOT do a course-based M.Sc., as those are just upgraded Honda Civics! You'll be under intense pressure to learn a lot fast, but you'll have the resources to do it. A B.Sc. will likely take longer and you'll spend a lot of time slacking off because undergrad courses are pretty damned easy. Also, a M.Sc. is a better credential to have than another B.Sc.. When you're choosing a prof, talk to the other grad-students. DO NOT just choose the guy who was nominated for a nobel prize. As the saying goes, "Happy students never won anyone a Nobel!".
• ninh 13y ago
  Universities tbh are more for meeting likeminded people nowadays: most of the stuff taught at CS can be learnt on your own given you're disciplined enough. Just to underline some of the points others have made, here is a short list of things I found most valuable from my CS degree: - Algorithms, Datastructures & Computational/space complexity (ADC). <-- This one is huge imo and will allow you to discern efficient code from inefficient ones. - Discrete Mathematics. It's the lingua franca when talking about CS and you will need it to understand ADC for example. It introduces set theory, graph theory and so forth, which are used in ADC/AI etc... to describe and solve problems. - Linear Algebra: if you ever want to work with 3d stuff, this one will be essential. It'll also work out nicely for 2d work, and seeing as you mentioned you've got a knack for UI work, you probably will appreciate this one. It'll allow you to get an understanding of for example affine transformations etc... You will need a computer graphics course too, but this is definitely a prerequisite course to do those. - Probability and statistics. I really hated this course (it's also one of the harder ones coincidentally), but once you "get it", you really do "get it". Ever wondered how gesture recognition works? Or how spam filters work? Well, the math required for this will be addressed here, together with the following subject. - Artificial Intelligence. Extremely useful if you're interested in game dev, or just want to learn to solve problems in a smart and efficient manner. It combines ADC with discrete mathematics with probability & statistics. - Calculus. If not for the math, it'll definitely make you look at things in a different way, which imo in turn, contributes to your way of looking at problems. Partial derivation / integrals and how it can relate to 3d surfaces for example. And let's not forget taylor series etc... It'll give you an idea of how mathematical functions such as sin(1) etc... can be implemented etc... - Operating systems, Computer Architecture/organization. Essential for understanding what happens under the hood. Allows you to reason about what the best code path is for solving a problem. Should you use the GPU for example instead of the CPU etc... and if so, why? etc... It also introduces models such as finite state automatons etc... which are also applicable in language processing for, say, compilers. And that brings us to the last, but certainly not least subject, my all time favorite: - Compiler construction. Gives you an insight in how languages are being processed, and how to design your own language and build a compiler for it. It should also give you additional insights on how runtimes/virtual machines work. The software engineering courses were more about processes, philosophies and patterns etc... and even though they're definitely useful, I think most experienced software engineers have already "got this". Either via books, company policy/culture or via experience. Again, these are my experiences, YMMV :) Good luck!
• ahmicro 13y ago
  Grow Beyond with Google: Guide for Technical Development https://docs.google.com/file/d/0B_Y4kz709TVwaVZfdnl3blI3UWs/edit?hl=en-GB&forcehl=1 https://docs.google.com/file/d/0B_Y4kz709TVwaVZfdnl3blI3UWs/...