Mathematics for Computer Science (Spring 2015) Prof. Albert R. Meyer and Prof. Adam Chlipala via MIT
Mathematics for Computer Science free videos and free material uploaded by Massachusetts Institute of Technology Staff .
Chapter 1: Propositions
Chapter 2: Patterns of proof
Chapter 3: Induction
Chapter 4: Number theory
Chapter 5: Graph theory
Chapter 6: Directed graphs
Chapter 7: Relations and partial orders
Chapter 8: State machines
Chapter 9: Sums and asymptotics
Chapter 10: Recurrences
Chapter 11: Cardinality rules
Chapter 12: Generating functions
Chapter 13: Infinite sets
Chapter 14: Events and probability spaces
Chapter 15: Conditional probability
Chapter 16: Independence
Chapter 17: Random variables and distributions
Chapter 18: Expectation
Chapter 19: Deviations
Chapter 20: Random walks
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.
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