Lecture 1

CIT 592
Discrete Math
Lecture 1
By way of introduction …
• Arvind Bhusnurmath
• There are no bonus points for pronouncing my last name
• 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
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
• Main website for announcements/readings
• Office hours and recitations
• My office ´â│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
• 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
• The mathematics of modern computer science is built
almost entirely on discrete math, in particular
combinatorics and graph theory