MIT OpenCourseWare

Browse materialsMIT 6.1200J · Spring 2024

Mathematics for Computer Science

Subjects: Computer Science · Mathematics · Science

Art: Palmer, Edward, 1803-1872, Figures 113-123. Plate Electrical Machines, 1840 · Public domain

Instructors: Prof. Erik Demaine, Dr. Zachary Abel, Dr. Brynmor Chapman
Term: Spring 2024
Level: Undergraduate
What's inside: 24 videos · 10 problem sets · 23 lecture notes · 1 reading · 32 other files · 1 web page
Materials open: Videos here · files on MIT OCW

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About this course

Source: MIT OpenCourseWare 6.1200J Mathematics for Computer Science, Spring 2024, Prof. Erik Demaine, Dr. Zachary Abel, Dr. Brynmor Chapman — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.

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Before you start

Prerequisites are not listed here. Check MIT's own syllabus for this course.

How this course was organized

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Materials by section

Grouped by section, as MIT organized them. Not sequenced or ordered.

Lecture Notes

23 files

Warm Up Problems

7 files

Problem Sets

Other materials from this course

22 video transcripts

MIT OpenCourseWare, Prof. Erik Demaine, Dr. Zachary Abel, Dr. Brynmor Chapman, 6.1200J Mathematics for Computer Science, Spring 2024.

License: CC BY-NC-SA 4.0 · Edition: Spring 2024 · Open the original course on OCW ↗

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Mathematics for Computer Science

Before you start

What's here, and what isn't

Not included here

Materials by section

Lecture Notes

Warm Up Problems

Problem Sets

Other materials from this course

Lecture 1: Predicates, Sets, and Proofs

Lecture 2: Contradiction and Induction

Lecture 3: Casework and Strong Induction

Lecture 4: State Machines

Lecture 5: Sums

Lecture 6: Asymptotics

Lecture 7: Recurrences

Lecture 8: Divisibility

Lecture 9: Modular Arithmetic

Lecture 10: Cryptography

Lecture 11: Graphs and Coloring

Lecture 12: Matching

Lecture 13: Connectivity and Trees

Lecture 14: Digraphs and DAGs

Lecture 15: Relations and Counting

Lecture 16: Counting Techniques

Lecture 17: More Counting Techniques

Lecture 18: Probability

Lecture 19: Conditional Probability

Lecture 20: Independence

Lecture 21: Random Variables

Lecture 22: Expectation

Lecture 23: Expectation and Variance

Lecture 24: Large Deviations: Chebyshev and Chernov Bound, Wrap Up

Problem Set 01

Problem Set 02

Problem Set 03

Problem Set 04

Problem Set 05

Problem Set 06

Problem Set 07

Problem Set 08

Problem Set 09

Problem Set 10