The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.
Prerequisites: Prerequisite: Open to graduate students in the CSE program, others with permission. Recommended Preparation: CSE 3500 or the equivalent. (RG5907)
Grading Basis: Graded
Introduction to the design and analysis of algorithms. The course will discuss fundamental design techniques and related issues such as amortized analysis, linear programming, network flow, NP-Completeness, approximation algorithms, randomized algorithms, advanced data structures, and parallel algorithms.
Last Refreshed: 30-OCT-20 05.20.18.831626 AM
|Term||Class Number||Campus||Instruction Mode||Instructor||Section||Session||Schedule||Enrollment||Location||Credits||Grading Basis||Notes|
|1208 6430 1 001||Fall 2020||6430||Storrs||In Person||Wu, Yufeng||001||Reg||TuTh 2:00pm‑3:15pm
|1213 16089 1 001||Spring 2021||16089||Storrs||Distance Learning||Bansal, Mukul||001||Reg||MoWe 5:00pm‑6:15pm
||4/50||No Room Required - Online||3.00||Graded|