## Mathematics for Computer Science: Discrete Mathematics

Title | Mathematics for Computer Science: Discrete Mathematics (50103) |
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Quarter | Summer 2016 |

Instructor | Geraldine Brady (gb52@uchicago.edu) |

Website | |

Syllabus | Course DescriptionThis course in an introduction to discrete mathematics oriented toward computer science. The course emphasizes mathematical proof and problem solving, employed on a variety of useful topics: logic; proof by induction; counting, factorials, and binomial coefficients; discrete probability; random variables, expected value, and variance; recurrences; graphs and trees; basic number theory; asymptotic notation, and rates of growth. On completion of the course, students will have been trained to think about and absorb mathematical concepts, to solve problems requiring more than standard recipes, and express mathematical notions precisely. They will be able to use ideas and techniques from discrete mathematics in subsequent courses in computer science, in particular courses in the design and analysis of algorithms, networks, numerical methods, software engineering, data analysis, data mining, and machine learning.
Topics covered include: logic and proof; mathematical induction; modular arithmetic; basic counting, permutations, combinations, binomial theorem, pigeonhole principle, inclusion/exclusion; discrete probability spaces, conditional probability, independence, Bernoulli trials, Bayes's theorem, random variables, expected value, variance, geometric and binomial distributions; graphs and trees; recurrences, methods of solving simple recurrences, asymptotic notation, and the master theorem. |

Prerequisites (Courses) | |

Prerequisites (Other) | Only MPCS students can register for this course. |

Satisfies | Math prerequisite requirement. |

Time | Tuesday 5:30-8:30pm (Lecture); Saturday 12-2pm (Problem-solving session) |

Location | Ryerson 276 |