Analysis of Algorithms (CSCI-261-02), Fall 2017-18

Instructor:   Ivona Bezakova, email: (please replace my_initials with ib)
Class meets:   Tu/Th 2:00-3:20, room (GOL)-2455

Office hours (tentative), when classes are in session: Tuesday/Thursday 11am-12pm and 3:30-4:30pm, office (GOL)-3645
Tutoring center: schedule (will be posted by week 2), staffed by students who took (and performed well in) theory-related courses in recent years

Piazza: you will receive an e-mail invitation to this discussion board (please use piazza for all class-related correspondence) - if you have not received the invitation by the end of the first week, please contact me on my regular CS email address

0. Homework and Reading Assigments

For information about topics covered in class, reading and homework assignments, follow this link.

1. Prerequisites

MATH-190 (Discrete Mathematics for Computing) and CSCI-243 (The Mechanics of Programming) or equivalent courses

2. Text

Highly recommended: Algorithm Design by Jon Kleinberg and Eva Tardos.
The assignments webpage (that will contain slides from the lectures):
Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein, 3rd ed. is a great text for further reading.

3. Course description and intended learning outcomes.

This course provides an introduction to the design and analysis of algorithms. It covers a variety of classical algorithms and data structures and their complexity and will equip students with the intellectual tools to design, analyze, implement, and evaluate their own algorithms.

Intended learning outcomes:

4. Grading Policy Grading scale: 88%-100%: A grades (91%-100% A, 88%-91% A-), 77%-88%: B grades (85%-88% B+, 80%-85% B, 77%-80% B-), 66%-77%: C grades (74%-77% C+, 69%-74% C, 66%-69% C-), 55%-66%: D, 0%-55%: F.
However, your overall grade cannot be more than one letter better than your average exam grade. Moreover, average exam grade F results in failing the class.

5. Topics 6. Technical issues