Professor | Office | |
K. Raven Russell | krusselc | ENGR 5328 |
For All Classes:
For Online and Hybrid Classes:
Topics include analyzing sequential and parallel algorithmic strategies such as greedy methods, divide and conquer strategies, dynamic programming, search and traversal techniques, and approximation algorithms; and analyzing specific algorithms falling into these classes, NP-Hard and NP-Complete problems.
Tentative topics to be covered include:
See the schedule (on Blackboard) for a more detailed topics list.
Formal Methods and Models (such as CS 330 or a similar course) and by entension Discrete Mathematics (in Math 125 or a similar course). Data Structures (such as CS310 or a similar course) and by extension multiple programming courses (such as CS 211 or a similar course). An undergraduate algorithms course is also helpful, but not required.
Below is a more detailed (but not exhaustive) list of topics which may "come back to haunt you":
Category | Percent |
Homework | 30% |
Midterm Exam | 30% |
Final Exam | 40% |
The following will be applied without rounding:
Small amounts of extra credit may be offered during the semester, but there will be no make-up or extra-credit assignments at the end of the semester; your grade should be a measure of your semester-long progress.