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| 1.
| [Basic algorithm design technique]
Understand basic techniques for designing algorithms, including the techniques of recursion, divide-and-conquer, and greedy. |
| 2.
| [Advanced algorithm design technique]
Understand advanced techniques for designing algorithms, including dynamic programming, network flow and problem reduction. |
| 3.
| [Correctness and time complexity]
Understand the techniques of proof by contradiction, mathematical induction and recurrence relation, and apply them to prove the correctness and to analyze the running time of algorithms. |
| 4.
| [Intractability]
Understand the mathematical criterion for deciding whether an algorithm is efficient, and know many practically important problems that do not admit any efficient algorithms. |
| 5.
| [Problem solving]
Able to apply the algorithm design techniques to design efficient algorithms for different kinds of problems |
Mapping from Course Learning Outcomes to Programme Learning Outcomes
| | PLO a | PLO b | PLO c | PLO d | PLO e | PLO f | PLO g | PLO h | PLO i | PLO j |
| CLO 1 | T,P | | | | | | | | | |
| CLO 2 | T,P | | | | | | | | | |
| CLO 3 | T,P | | T,P | | | | | | | |
| CLO 4 | T,P | | T,P | | | | | | | |
| CLO 5 | | | T,P | | | | | | | |
T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to
here.
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| Syllabus |
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Calendar Entry:
The course studies principles of algorithm design and the analysis of sophisticated algorithms (regarding proof of correctness and time complexity). Topics include divide-and-conquer, dynamic programming, greedy algorithms, graph algorithms, network flow, geometric algorithms, and NP-completeness. The course puts emphasis on mathematical rigor; it expects students to figure out the mathematics and logic that make algorithms work. Students can form pairs to discuss the assignments and are required to write rigorous proofs of correctness and analysis independently.
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Detailed Description:
| Basic algorithm design technique |
Mapped to CLOs
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| Divide and Conquer | 1, 3, 5 |
| Greedy algorithms | 1, 3, 5 |
| Graph algorithms | 1, 3, 5 |
| Advanced algorithm design technique |
Mapped to CLOs
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| Dynamic programming | 2, 3, 5 |
| Network flow | 2, 3, 5 |
| Intractability |
Mapped to CLOs
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| Problem reduction and NP-completeness | 2, 3, 4, 5 |
| Approximation Algorithms | 3, 4, 5 |
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Assessment:
Continuous Assessment:
50%
Written Examination:
50%
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| Teaching Plan |
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Please refer to the corresponding Moodle course.
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| Moodle Course(s) |
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