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CIT 592 Discrete Math Lecture 1 By way of introduction … • Arvind Bhusnurmath • There are no bonus points for pronouncing my last name correctly • Please call me Arvind • New to teaching at Penn • However, not new to Penn. Graduated 2008 • https://www.grasp.upenn.edu/ • http://www.youtube.com/watch?v=4ErEBkj_3PY (my fav TED talk) • Worked 5 years at http://www.predictivetechnologies.com/ Who is this course for? • MCIT students • Objective : To learn fundamentals of discrete math in order to understand algorithm complexity, proving a program works, graph theory etc Textbook and resources • • • Textbook – Discrete Mathematics for Computer Scientists by Stein et al. Intend to follow textbook fairly closely but might skip some parts Resources • • • Discrete Mathematics by Rosen et al. (a more mathematical treatment of the topic) Elements of discrete mathematics by Liu et al. (a classic) Mathematics: A discrete introduction – Scheinerman Logistics • Main website for announcements/readings http://www.seas.upenn.edu/~bhusnur4/cit592/ • Office hours and recitations • My office Moore/Levine/GRW 268. Opposite Weiss Tech house. Schedule (might change…) • Counting principles – Chapter 1 • Proof techniques – Chapter 3 + some additional material • Induction – Chapter 4 • Probability – Chapter 5 • Graph Theory – Chapter 6 • Time permitting we will cover number theory and RSA encryption – Chapter 2 Exams, homeworks etc • Homework handed out/posted every Thursday • Due next Thursday at the start of class. • Deadlines will be strictly enforced • If you do have an emergency, send me email or have one of your classmates send me email • Grading • 2 midterms 20% each • 1 final 30% • Homeworks 30% How to turn in assignments • Print out/handwritten assignments • Word/Latex submissions encouraged • If you are submitting handwritten solutions please write neatly • The rule of ‘If I can’t read it, you haven’t written it’ will be applied Why should I do this math stuff??? Why should I do this course • Discrete math teaches mathematical reasoning and proof techniques. • The mathematics of modern computer science is built almost entirely on discrete math, in particular combinatorics and graph theory