The full course textbook, Mathematics for Computer Science, is available for download (PDF 5.9MB).

Unit 1: Proofs
1 1.1 Intro to Proofs Chapter 1.1–1.6 (PDF)
2 1.2 Proof Methods Chapter 1.7–1.9 (PDF)
3 1.3 Well Ordering Principle Chapter 2.1–2.3 (PDF)
4 1.4 Logic & Propositions Chapter 3.1–3.5 (PDF)
5 1.5 Quantifiers & Predicate Logic Chapter 3.6 (PDF)
6 1.6 Sets Chapter 4.1–4.2 (PDF)
7 1.7 Binary Relations Chapter 4.3–4.5 (PDF)
8 1.8 Induction Chapter 5.1–5.3 (PDF)
9 1.9 State Machines - Invariants Chapter 5.4 (PDF)
10 1.10 Recursive Definition Chapter 6 (PDF)
11 1.11 Infinite Sets Chapter 7 (PDF)
Unit 2: Structures
12 2.1 GCDs Chapter 8.1–8.5 (PDF)
13 2.2 Congruences Chapter 8.6–8.9 (PDF)
14 2.3 Euler's Theorem Chapter 8.10 (PDF)
15 2.4 RSA Encryption Chapter 8.11–8.12 (PDF)
16 2.5 Digraphs: Walks & Paths Chapter 9.1–9.4 (PDF)
17 2.6 Directed Acyclic Graphs Chapter 9.5 (PDF)
18 2.7 Partial Orders and Equivalence Chapter 9.5–9.11 (PDF)
19 2.8 Degrees & Isomorphism Chapter 11.1–11.4 (PDF)
20 2.9 Coloring & Connectivity Chapter 11.7–11.9 (PDF)
21 2.10 Trees Chapter 11.9–11.10 (PDF)
22 2.11 Stable Matching Chapter 11.6 (PDF)
Unit 3: Counting
23 3.1 Sums & Products Chapter 13.1–13.5 (PDF)
24 3.2 Asymptotics Chapter 13.7 (PDF)
25 3.3 Counting with Bijections Chapter 14.1–14.2 (PDF)
26 3.4 Repetitions & Binomial Theorem Chapter 14.4–14.7 (PDF)
27 3.5 Pigeonhole Principle, Inclusion-Exclusion Chapter 14.8 (PDF)
Unit 4: Probability
28 4.1 Intro to Discrete Probability Chapter 16.1–16.5 (PDF)
29 4.2 Conditional Probability Chapter 17.1–17.5 (PDF)
30 4.3 Independence & Causality Chapter 17.7–17.8 (PDF)
31 4.4 Random Variables, Density Functions Chapter 18.1–18.3 (PDF)
32 4.5 Expectation Chapter 18.4–18.5 (PDF)
33 4.6 Deviation: Markov & Chebyshev Bounds Chapter 19.1–19.3 (PDF)
34 4.7 Sampling & Confidence Chapter 19.4–19.5 (PDF)
35 4.8 Random Walks & Pagerank Chapter 20.2 (PDF)