# DMMR: Course Schedule and Lecture Slides 2018

Lecture slides will typically be available from this web page a day or two before the lecture. The slides from last year will give a good idea about what's coming up.
WeekLectures Readings
1 Sep 17: Lecture 1: Introduction and Course Admin
Sep 18: Lecture 2: Predicates, Quantifiers and Proof Techniques
Sep 20: Lecture 3: Predicates, Quantifiers and Proof Techniques
Rosen Chapter 1
2 Sep 24: Lecture 4: Sets, Functions, Relations, Sequences and Sums
Sep 25: Lecture 5: Sets, Functions, Relations, Sequences and Sums
Sep 27: Lecture 6: Sets, Functions, Relations, Sequences and Sums
Rosen Sections 2.1-2.4, 9.1, 9.4 and 9.5
3 Oct 01: Lecture 7: Relations, Sequences and Sums
Oct 02: Lecture 8: Cardinality
Oct 04: Lecture 9: Cardinality
Rosen Sections 9.4, 9.5 and 2.5.
4 Oct 09: Lecture 10: Induction
Oct 10: Lecture 11: Induction
Oct 12: Lecture 12: Arithmetic Modulo m, Primes
Rosen Sections 5.1, 5.2, then 4.1.
5 Oct 15: Lecture 13: Greatest Common Divisors
Oct 16: Lecture 14: Multiplicative Inverses and Some Cryptography
Oct 18: Lecture 15: Multiplicative Inverses and Some Cryptography
Rosen Sections 4.3, 4.4 and 4.6
6Oct 22: Lecture 16: Basic Counting, and the Pigeonhole Principle
Oct 23: Lecture 17: Permutations & Combinations, Binomial Coefficients
Oct 25: Lecture 18: Generalized Permutations & Combinations
Rosen chapter 6
7Oct 29: Lecture 19: Graphs: basic definitions and examples
Oct 30: Lecture 20: Bipartite Graphs and Matching
Nov 1: Lecture 21: Graph Isomorphism; Paths and Connectivity; Euler paths/circuits
Rosen chapter 10
8 Nov 5: Lecture 22: Euler and Hamiltonian paths/circuits (continued); shortest paths;
Nov 6: Lecture 23: Shortest Paths and Dijkstra's algorithm; Graph Coloring
Nov 8: Lecture 24: Trees
Rosen chapter 10 & 11
9 Nov 12: Lecture 25: Introduction to Discrete Probability; some important distributions;
Nov 13: Lecture 26: Conditional probabability; Bayes' theorem
Nov 15: Lecture 27: Random variables, Expectation, and Variance
Rosen chapter 7
10 Nov 19: Lecture 28: Markov's and Chebyshev's Inequalities; Examples in probability: the birthday problem;
Nov 20: Lecture 29: Examples in probability: ramsey numbers
Nov 22: Lecture 30: review lecture
Rosen chapter 7

#### Study guide

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