In this class we will cover a number of ideas and techniques useful for designing and analyzing data structures and algorithms. In particular, we will introduce techniques for analyzing upper bounds for algorithms and lower bounds for problems. Problem areas include sorting, graphs, dynamic programming, combinatorial algorithms, computational geometry, encryption, parallel models, and NP-Completeness.
The prerequisites for this class are Data Structures (CSE 2320) and Theoretical Concepts in Computer Science and Engineering (CSE 3315). Please contact the CSE graduate advisor, Dr. Yerraballi (email@example.com), if you have questions about the prerequisites or your technical background.
The textbook for this class is Cormen, Leiserson, Rivest, and Stein, Introduction to Algorithms, Second Edition, MIT Press, 2001. This book can be purchased directly from the publisher at http://mitpress.mit.edu/catalog/item/default.asp?sid=7B25DB71-BAA5-4AE8-A005-10CD494618DE&ttype=2&tid=8569.
The instructor for this online class is Diane Cook. She can be reached by email at firstname.lastname@example.org or by phone at (817) 272-3606. The TA for this class is Arjun Dasgupta. Arjun can be reached by email at email@example.com and will hold regular office hours Thursdays from 3 to 5 in 100 Engineering Office Building. If you need to physically meet with somebody on campus, please set up an appointment with myself or the TA.
Diane Cook is a Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington. Dr. Cook received her B.S. from Wheaton College in 1985, and her M.S. and Ph.D. from the University of Illinois in 1987 and 1990, respectively. Dr. Cook's research interests include artificial intelligence, machine planning, machine learning, data mining, robotics, and parallel algorithms for artificial intelligence.
The grade distribution for this class is shown below. With the first quiz you will be asked to provide a pseudonym consisting of six letters and/or digits. This pseudonym can be used throughout the remainder of the semester to verify your scores and compare your weighted semester total with the class average.
If you encounter difficulties using this machine or have questions, send email to firstname.lastname@example.org or call ACS directly at (817) 272-2208.