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Course description
Syllabus
Course policies
Lecture notes
Projects and Homeworks
Additional resources
Reading list
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Course Information
- Course id: 21190120
- Course name: Algorithm design and analysis
Instrutor
Class times and places
- Lecture Time & Place: Tues day (9-10 session), Caoguangbiao West 104, Yuquan Campus
Thursday(7 - 8 session), Caoguangbiao West 104
- Practice time: Thursday (9-10); Place: College Lab (Caoguangbiao West 503)
Course description
- This course provides elementary introduction to algorithm design and analyis. Topics include: mathematics foundation, divided-and-conquer, dynamic programming, greedy method, NP-completeness complexity, approximation algorithm, randomized algorithm, online algorithm, et al.
- Students at the end of course should be able to do the following:
1) Understand the concepts and skills of algorithm design
2) Implimental some wellknown algorithms
3) Analyze the performance of algorithms
Syllabus
- Prerequisite: Data Structure, C/C++ Programming language
- Textbooks: Introduction to algorithms, Second Edition.
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein. The MIT Press.
ISBN: 0262032937. 2001.
- References:
1) Algorithm Design. Jon Kleinberg, Eva Tardos, Addison Wesley. ISBN: 0-321-29535-8 2005.
2) Algorithms. S. Dasgupta, C.H. Papadimitriou, and U. V. Vazirani. May 2006.
3) Combinatorial Algorithms. Jeff Erickson. University of Illinois, Urbana-Champaign. Lecture Notes. Fall 2002.
Course policies
- Grading: Grades for the course will be based on the following weighting
1) Class attendance: 10%
2) Homework: 25%
3) Project: 20%
4) Final Exam: 45%
- Project:
1)Assignments are due in class as noted in the syllabus and web page.
Project assignments turned in within the due dates, there is no extention of the deadline.
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