Analysis of Algorithms (CSCI-261-02), Fall 2014-15

Instructor:   Ivona Bezakova, email: (please replace my_initials with ib)
Class meets:   Tu/Th 2:00-3:15, room (GOL)-1620
No meetings:: August 26 and August 28 (instructor is out of town at a conference) - to make up for the missed time, there will be out-of-class review sessions for the midterm and final exams.
Office hours (tentative), starting on September 2: Tuesday 3:15-4pm, Wednesday 10am-12pm, and Thursdays 1-1:50pm, office (GOL)-3645
Tutoring center: schedule, staffed by students who took (and performed well in) theory-related courses in recent years

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) or equivalent and CSCI-243 (The Mechanics of Programming)

2. Text

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 (optional).

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