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Education

Ask Slashdot: Online, Free Equivalent To a CompSci BS? 197

Posted by timothy
from the yes-but-how dept.
An anonymous reader writes "I am a middle school math teacher and I also run a programming club. I recent completed my M.Ed in math education and was inspired to try to do the new GT online MS in Computer Science in a couple of years. I have some background in programming: two intro to comp sci courses, Java, C++, Python, the main scripting languages, and a bunch of math background. I also read through this great article on getting these pre-requisites completed through Coursera but unfortunately you need to wait for courses to enroll. I would like to just learn these on my own time, no credit necessary. Suggestions?"
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Ask Slashdot: Online, Free Equivalent To a CompSci BS?

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  • Re:MIT (Score:3, Interesting)

    by Anonymous Coward on Sunday March 09, 2014 @02:21PM (#46440841)

    Parts of it are painful to do on your own. The emphasis on Scheme and recursive layers of abstraction, and the last 20 years of objected oriented nonsense wasted space that is is the descendant of early LISP research and makes Java programmers so *bad* at performance programming can take a decade to *unlearn* to do anything reliably or in real time. "Object Oriented" is the enemy of understanding why things break.

    I'd still recommend the online courses from MIT, in general, and spending time with toys from Adafruit. There are a stack of toys there that can give a grounding in basic electronics, small system configuration, and microprogramming far beyond any course work done without an actual lab to play in.

  • Re:Donald Knuth (Score:3, Interesting)

    by jmcbain (1233044) on Sunday March 09, 2014 @02:36PM (#46440899)
    "Computer Science" is a very broad field covering both theory and programming. Here are some great books:

    -- Introduction to Algorithms, 3rd ed., by Cormen, et al. ABSOLUTELY MUST-READ.
    -- Computer networking: a top-down approach, by Kurose and Ross. Great book; skips the physical layer.
    -- The C Programming Language, by Kernighan and Ritchie. This is the one book you need on programming language pragmatics.
    -- Modern Operating Systems, by Tanenbaum.
    -- An Introduction to Statistical Learning: with Applications in R, by James, et al. Have not read this machine learning book myself, but the Amazon reviews say it's great.

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