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Introduction to Logic

Coursera · Stanford University · 1 HN points · 5 HN citations

This course is an introduction to Logic from a computational perspective. It shows how to encode information in the form of logical sentences; it shows how to reason with information in this form; ...

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Hacker News Comments about Introduction to Logic

All the comments and stories posted to Hacker News that reference this course.
Sep 25, 2015 Houshalter on The Incredible Proof Machine
There is a coursera course on formal logic which starts in 3 days and covers this kind of stuff:

They have a very nice proof editor: And some other logic tools:

This system is pretty neat though.

EDIT: I'm having trouble with this. I can not get Or Introduction or Or Elimination to work. I have no idea what it where the inputs are supposed to go or why it doesn't accept it as valid. I did figure out how to do assumption, but it wasn't immediately obvious and is kinda clunky.

Aug 10, 2015 ky3 on Parallels Between Math and Software Engineering
You can play creatively in a particular nexus of math and software engineering called Djinn [0], the Haskell program that writes your Haskell programs for you.

1. An ancestor of Djinn is automated theorem proving. Why can't machines prove math theorems for us? This quest goes back to the dawn of computing science.

2. A more recent development is the Curry-Howard Correspondence. Programming in a (typed) FP language is like playing tetris. Solving symbolic logic problems [1] is also like playing tetris. Djinn exposes the connection in a REPL you can play with. And see how the computer plays tetris for you!

3. Don't want to install Djinn? No problem, just hop over to the Haskell IRC [2]. Lambdabot has a working Djinn plugin.




Dec 09, 2014 osoba on Ask HN: How or where to begin learning mathematics from first principles?
I will try to list resources in a linear fashion, in a way that one naturally adds onto the previous (in terms of knowledge)


First things first, I assume you went to a highschool, so you don't have a need for a full pre-calculus course. This would assume you, at least intuitively, understand what a function is; you know what a polynomial is; what rational, imaginary, real and complex numbers are; you can solve any quadratic equation; you know the equation of a line (and of a circle) and you can find the point that intersects two lines; you know the perimiter, area and volume formulas for common geometrical shapes/bodies and you know trigonometry in a context of a triangle. Khan Academy website (or simple googling) is good to fill any gaps in this.


You would obviously start with calculus. Jim Fowlers Calculus 1 is an excellent first start if you don't know anything about the topic. Calculus: Single Variable is the more advanced version which I would strongly suggest, as it requires very little prerequisites and goes into some deeper practical issues.

By far the best resource for Linear Algebra is the MIT course taught by Gilbert Strang If you prefer to learn through programming, might be better for you, though this is a somewhat lightweight course.


After this point you'd might want to review single variable calculus though a more analytical approach on MIT OCW as well as take your venture into multivariable calculus

Excellent book for single variable calculus (though in reality its a book in mathematical analysis) is Spivaks "Calculus" (depending on where you are, legally or illegally obtainable here (as are the other books mentioned in this post)). A quick and dirty run through multivariable analysis is Spivaks "Calculus on Manifolds".

Another exellent book (that covers both single and multivar analysis) is Walter Rudins "Principles of Mathematical Analysis" (commonly referred to as "baby rudin" by mathematicians), though be warned, this is an advanced book. The author wont cradle you with superfluous explanations and you may encounter many examples of "magical math" (you are presented with a difficult problem and the solution is a clever idea that somebody magically pulled out of their ass in a strike of pure genius, making you feel like you would have never thought of it yourself and you should probably give up math forever. (Obviously don't, this is common in mathematics. Through time proofs get perfected until they reach a very elegant form, and are only presented that way, obscuring the decades/centuries of work that went into the making of that solution))

At this point you have all the necessery knowledge to start studying Differential Equations

Alternativelly you can go into Probability and Statistics


If you have gone through the above, you already have all the knowledge you need to study the areas you mentioned in your post. However, if you are interested in further mathematics you can go through the following:

The actual first principles of mathematics are prepositional and first order logic. It would, however, (imo) not be natural to start your study of maths with it. Good resource is and possibly

For Abstract algebra and Complex analysis (two separate subjects) you could go through Saylors courses (sorry, I didn't study these in english).

You would also want to find some resource to study Galois theory which would be a nice bridge between algebra and number theory. For number theory I recommend the book by G. H. Hardy

At some point in life you'd also want to go through Partial Differential Equations, and perhaps Numerical Analysis. I guess check them out on Saylor

Topology by Munkres (its a book)

Rudin's Functional Analysis (this is the "big/adult rudin")

Hatcher's Algebraic Topology


It is, I guess, natural for mathematicians to branch out into:

[Computer/Data Science]

There are, literally, hundreds of courses on edX, Coursera and Udacity so take your pick. These are some of my favorites:

Artificial Intelligence

Machine Learning

The 2+2 Princeton and Stanford Algorithms classes on Coursera

Discrete Optimization

Convex Optimization


Jun 03, 2013 keiferski on Why does France insist school pupils master philosophy?
Honestly the best source I've come across is a book, Understanding Symbolic Logic by Klenk. But here are some decent online resources:

Apr 10, 2012 mikek submitted Introduction to Logic (1 points, 0 comments)
Mar 31, 2012 aseembehl on Stanford's Coursera announces free Compilers, Automata and Logic courses.
Stanford's Coursera launches 3 more CS classes.

Compilers by Professor Alex Aiken

Automata by Professor Jeff Ulman

Intro. to Logic by Professor Michael Genesereth

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