Department and Course Number:
M-W 2:10 – 3:30
1.0 General Course Information
1.1 Current Catalog Description:
Techniques for designing efficient algorithms, analyzing their complexity and applying these algorithms to a broad range of application settings. Methods for recognizing and dealing with hard problems are studied.
1.2 Prerequisites by Topic:
1.3 Course Staff
Office: LKD 2112C
Phone: 412-965 6778
Contact Email: email@example.com
Office Hours: Wed. 6pm
Teaching Assistants: None
2.0 Learning Resources
2.1 Required Text
Jeffrey McConnell. Analysis of Algorithms: An Active Learning Approach. Jones & Bartlett. 3rd Edition, 2007.
2.2 Other References:
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein. Introduction to Algorithms. McGraw Hill, 2nd edition, 2001.
2.3 Department Resources
Laboratories: (obtain account logins from Mr. Derssie Mebratu – firstname.lastname@example.org)
3.0 Aims, Objectives, Program Outcomes
3.1 Course Aims
This course introduces the concept of analyzing and comparing algorithms relative to their efficiency in both time and space. Where other courses treat algorithms as either working or non-working, this course considers how well algorithms work based on the size and nature of the problem.
4.1 Assessment Summary
Daily Quiz 40%
4.2 Course Grading
>= 80% A
<80% and >= 70% B
<70% and >= 60% C
<60% and >= 50% D
4.3 Policy on late projects, research papers, and make-up exams
Late assignments will be given ZERO credit. NO make-up exams will be given unless there is a bona fide written doctor’s excuse. In the event that such an excuse is accepted, the deadline will be extended the number of days specified in the excuse. A penalty of 1% of the final grade will be assessed for each unexcused absence.
4.4 Plagiarism Policy
The Americans with Disabilities Act requires institutions to accommodate the needs of persons with disabilities. If you need special arrangements such as sign language interpreters or audiotapes of lectures, please make an appointment to see me.