Algorithms (Section 2)

Title Algorithms (Section 2) (55001-2)
Quarter Autumn 2021
Instructor Geraldine Brady (gb52@uchicago.edu)
Website

Syllabus

**Cannot take this course in your last quarter in the program**

Course Description

The course is an introduction to the design and analysis of efficient algorithms, with emphasis on design techniques. Algorithmic problems include sorting and searching, discrete optimization, and algorithmic graph theory. Design techniques include divide-and-conquer methods, dynamic programming, randomization, greedy methods, as well as the design of efficient data structures. Methods of algorithm analysis include asymptotic notation, evaluation of recurrences, and the concepts of polynomial-time algorithms. Students who complete the course will have demonstrated the ability to use divide-and-conquer methods, dynamic programming methods, and greedy methods when an algorithmic design problem calls for such a method. They will have learned the design strategies employed by the major sorting algorithms and the major graph algorithms, and will have demonstrated the ability to use these design strategies to solve algorithm problems when appropriate. They will have derived and solved recurrences describing the performance of divide-and-conquer algorithms, analyzed the time and space complexity of dynamic programming algorithms, and analyzed the efficiency of the basic graph algorithms, using asymptotic analysis.

Course Content
Topics covered include: sorting and searching; divide-and-conquer; randomization; dynamic programming; hash tables and binary search trees; graph search; shortest paths; minimum spanning trees; and network flow.

Coursework
Lectures: Students are responsible for all material presented in lectures.

Class sessions: Course material for the current week and assigned homework from the previous week will be discussed at the class meetings. Class participation grade is based on participation at class sessions.

Homework: Weekly homework assignments are posted after class and are due the day before class on the following week. Homework must be submitted electronically. Homework will include a weekly programming assignment in Python.

Exams: There will be four quizzes, a midterm exam, and a final exam.  There will be no make-up exams.

Course grade
The course grade will be based on homework, quizzes, and exams:

  • Homework: 5%
  • Quizzes: 20% (5% for each quiz)
  • Midterm: 25%
  • Final: 45%
  • Class participation: 5%

Textbook
Introduction to Algorithms (Third Edition) by T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein (ISBN 978-0-262-03384-8).

Prerequisites (Courses)

MPCS 50103 Discrete Math (Immersion Math) OR a passing score on the MPCS Mathematics Placement exam.
Immerse Programming (completed) or Core programming (concurrently taking).

Prerequisites (Other)

Satisfies

Core Theory

Time

TBD

Location

TBD