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Mathematics for Computer Science

cs.princeton.edu

204 pointsepenn23 comments

For those interested, I'm almost certain that this is from MIT's 6.042 (Mathematics for Computer Science) class: http://courses.csail.mit.edu/6.042/spring12/ There is a publicly accessible, most-recent-draft of the text at http://courses.csail.mit.edu/6.042/spring12/mcsfull.pdf

> Here is another wildly fun 6.042 game that’s surely about to sweep the nation!

Makes sense!

Yes - these notes are definitely from 6.042. I TA'ed the class a couple of times as these notes were being developed. In my opinion, they are fantastic. Entertaining and engaging, while still maintaining an appropriate level of mathematical rigor.

Has anyone read both this and Knuth's Concrete Mathematics? http://www.amazon.com/Concrete-Mathematics-Foundation-Comput... How do they compare with each other?

In the early paragraphs, it shows:

∀ n ∈ N n2 + n + 41

It goes on to tell what ∀ means, and what N means, but excludes ∈.

This tells me there is a level of maths prerequisites required. For those of us who had liberal arts backgrounds with very little math who are programmers by sweat and knack, where can one go to get enough training to be ready to read something like this? I'd love to get through it and finally feel I'm on equal footing with some of my CS-trained peers (and actually be able to leverage the concepts at work) but seeing this early in the book leads me to believe I need some prerequisites first.

Thanks for your advice.

By the way I did have algebra 1 and 2, geometry, business calculus, and statistics, but it's been a looooooooooong time and at this point it's as if I didn't.

This is just a little set notation, ∈ means 'is an element of' the set after the symbol. So for example, ∀ n ∈ N n^2 + n + 41 means 'for every n in the set of real numbers, n^2+n+41'. Reading the linked story, that's a proposition for the definition of prime numbers setting up for a proof. You usually learn set notation, proofs, induction, relations, and most of the stuff before probability I scanned in the Table of Contents there in a discrete math course. Many also cover probability, but ymmv.

Look at the version in the comment posted by joshma: http://courses.csail.mit.edu/6.042/spring12/mcsfull.pdf

You must not have been the only person to notice this. The definition is on pg 6 in the pdf above.

Awesome...thanks. So I suppose these should be used instead of the originally posted pdf? Thanks again!

Another good resource are the readings [1] from OCW's Mathematics for Computer Science

[1] http://ocw.mit.edu/courses/electrical-engineering-and-comput...

Only reason this shows up as princeton.edu is that this text is used for several Math for CS classes at Princeton. Good text, I learned a lot!

Thanks for this.

I feel I can now go back and cover all the math i've forgotten since the first couple CS years (only a couple years ago!). I'm not really sure if it is worth the time from a practical standpoint, however I always feel slightly slower than other students when it comes to algorithm-related classes.

Hopefully this should get me up to speed again!

This has nothing to do with the quality of the text, and I appreciate someone using not-computer-modern for a TeX-ed text, but the capital T's are just strange.

Someone else here taking "Design of Algorithms I"?

http://www.reddit.com/r/algoclass/

Also join us in #algo-class on Freenode IRC.

Noticed this wasn't mentioned in the subreddit anywhere, so I posted about it. Thanks for the heads up!

Anyone knows if there is a .epub version or something more ebook-reader friendly?

Really nice and would be even better if it covered information theory too.

Anyone know of an online course following this book?

This is a helpful resource!

thank you, I was looking for something like this

I have to say that my favourite book ever on Computer Science Mathematics is actually Applied Mathematics for Database Professionals, by APress. It gave me an extremely thorough understanding of logic, set theory, and disabused me of my incorrect notion that relational databases were because of ER diagrams :-)

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