CS 70 at UC Berkeley

Discrete Mathematics and Probability Theory

Lecture: TuTh 12:30-2pm, Wheeler 150

Professor Babak Ayazifar

ayazifar (at) berkeley (dot) edu

Office Hours: TBD

Professor Anant Sahai

sahai (at) eecs (dot) berkeley (dot) edu

Office Hours: Tu/Th 2-3, Cory 258

Week 1 Overview

More Induction, Stable Matching

Week 2 Overview

Stable Matching, Graphs

Week 3 Overview

Modular Arithmetic, Public Key Cryptography (RSA)

Week 4 Overview

RSA, Polynomials, Secret Sharing

Week 5 Overview

Secret Sharing, Error Correcting Codes

Week 6 Overview

Error Correcting Codes, Counting

Week 7 Overview

Computability, Counting, Discrete Probability

Week 11 Overview

Concentration Inequalities, Polling, Intro to Continuous Probability


The discussion sections are specifically designed to consolidate the material covered in lectures and in the notes. It is highly recommended that you attend both discussions each week. You may attend any discussion section, but we recommend that you settle on a weekly two-section pair (with the same TA) as early as possible in the semester. If a particular section is too full, then students will be admitted on a first-come first-served basis and others will have to attend an alternative section. All sections are equivalent: they all cover the same material. See Policies for more information.



There will be weekly required homeworks, again designed to consolidate your understanding of the course material. It is highly recommended that you attempt all homeworks. Your lowest two homework scores will be dropped, but these drops should be reserved for emergencies. No additional allowances will be made for late or missed homeworks: please do not contact us about missed homeworks or late submissions. See Policies for more information.


Lecture Schedule

  • Lecture 0A (1/21): Introduction & Logic (Note 0Note 1Note 2)
  • Lecture 0B (1/23): Proofs (Note 3)
  • Lecture 1A (1/28): Induction (Note 4)
  • Lecture 1B (1/30): Stable Matching (Note 5)
  • Lecture 2A (2/4): Stable Matching (Note 5)
  • Lecture 2B (2/6): Graphs (Note 6)
  • Lecture 3A (2/11): Modular Arithmetic (Note 7)
  • Lecture 3B (2/13): Bijections/FLT, CRT (Note 7Note 8)
  • Lecture 4A (2/18): RSA, Polynomials (Note 8)
  • Lecture 4B (2/20): Polynomials, Secret Sharing (Note 9)
  • Lecture 5A (2/25): Secret Sharing, Error Correcting Codes (Note 9Note 10)
  • Lecture 5B (2/27): Polynomials, Secret Sharing (Note 10)
  • Lecture 6A (3/3): Counting (Note 11)
  • Lecture 6B (3/5): Counting II (Note 11)
  • Lecture 7A (3/10): Computability, Counting (Note 12)
  • Lecture 7B (3/12): Intro to Discrete Probability (Note 13)
  • Lecture 8A (3/17): Inclusion-Exclusion, Conditional Probability (Note 14)
  • Lecture 8B (3/19): Conditional Probability, Union Bound (Note 14Note 18)
  • Lecture 9A (3/31): Random Variables, Discrete Probability Distributions (Note 15Note 19)
  • Lecture 9B (4/2): Random Variables, Expectation (Note 15Note 19)
  • Lecture 10A (4/7): Review (Note 15Note 19)
  • Lecture 10B (4/9): Expectation, Variance (Note 15Note 19)