This course will cover algorithms for a variety of problems, as well as general algorithm design and analysis techniques such as divide-and-conquer, dynamic programming, and greedy algorithms. Specific topics include algorithm analysis, recurrences and asymptotic analysis; searching, sorting; algorithms for fundamental graph problems, such as depth-first search,connected components,topological sort,shortest paths.
Algorithms (CS 301)
Programs\Type | Required | Core Elective | Area Elective |
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BS-Computer Science & Eng. | * | ||
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CONTENT
OBJECTIVE
To prepare students 1) to analyze an algorithm's performance by asymptotic analysis methods, 2) to understand the role of data structures and programming paradigms on the performance of algorithms, and 3) to design efficient algorithms taking into account these important factors.
LEARNING OUTCOME
The students are expected to be able to analyse algorithms' resource usage by using asymptotic analysis and asymptotic notations.
The students are expected to be able identify the algorithm design technique used by a given algorithm such as divide-and-conquer, dynamic programming, greedy, etc.).
The students are expected to be able to use these algorithm design techniques to develop new algorithms for simple computational problems.
The students are expected to be aware of some common computational problems and some known algorithms for these problems.
The students are expected to know that there are limits of algorithmic approaches to the computational problems.
The students are expected to be able to design tests to analyse the correctness and the performance of practical implementations of algorithms.
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ASSESSMENT METHODS and CRITERIA
Percentage (%) | |
Final | 30 |
Midterm | 30 |
Assignment | 20 |
Group Project | 20 |
RECOMENDED or REQUIRED READINGS
Textbook |
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, "Introduction to Algorithms", The MIT Press |