This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.

Syllabus

Lec 1 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 2 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 3 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 4 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 5 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 6 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 7 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 8 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 9 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 10 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 11 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 12 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
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Lec 14 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 15 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 16 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 17 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 18 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 19 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
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Lec 21 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
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Lec 24 | MIT 6.042J Mathematics for Computer Science, Fall 2010.
Lec 25 | MIT 6.042J Mathematics for Computer Science, Fall 2010.

Taught by

Prof. Albert R. Meyer and Prof. Adam Chlipala

Reviews

4.5 rating, based on 2 Class Central reviews

Start your review of Mathematics for Computer Science

Rohit Rawool

The Mathematics for Computer Science course from MIT is one of the most intellectually rewarding and rigorous introductions to discrete mathematics available online. Designed by Professors Eric Lehman, F. Thomson Leighton, and Albert R. Meyer, it pr…

The Mathematics for Computer Science course from MIT is one of the most intellectually rewarding and rigorous introductions to discrete mathematics available online. Designed by Professors Eric Lehman, F. Thomson Leighton, and Albert R. Meyer, it provides a solid mathematical foundation for anyone pursuing computer science, algorithms, or data structures.

💡 What I Liked

Comprehensive Coverage: It covers essential topics like logic, proofs, set theory, combinatorics, graph theory, relations, and number theory — all deeply relevant to computer science.

Emphasis on Proofs: The course focuses heavily on mathematical reasoning and proof techniques, helping you think more rigorously and analytically.

Authentic MIT Material: The lecture notes, assignments, and exams are directly from MIT’s undergraduate curriculum, giving a true academic experience.

Free and Self-Paced: Everything is freely available through MIT OCW, making high-quality education accessible to everyone.

⚙️ What Could Be Challenging

The mathematical rigor can be demanding, especially for those new to formal proofs or discrete math.

Since it’s self-paced, it requires discipline and self-motivation to complete without instructor guidance.

Some lectures assume familiarity with abstract reasoning — it’s not a casual “intro” course.
Shubham Kumar

The "Mathematics for Computer Science" online course from MIT is an exceptional resource for anyone delving into the intersection of math and computer science. Covering discrete mathematics, logic, combinatorics, and graph theory, it provides a solid foundation for algorithm design, cryptography, and computational complexity. The lectures are comprehensive, well-structured, and complemented by challenging problem sets to test understanding. As a free resource, its accessibility is unparalleled, though it demands strong commitment due to its rigor. Highly recommended for students and professionals looking to enhance their theoretical understanding of computer science concepts. A top-rated course for its depth and clarity!

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