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COMPUTER ENGINEERING (MS) (ENGLISH) PROGRAMME
COURSE DESCRIPTION
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Name of the Course Unit
| Code
| Year
| Semester
| In-Class Hours (T+P)
| Credit
| ECTS Credit
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EVOLUTIONARY OPTIMIZATION STRATEGIES |
CMP511 |
1 |
2 |
3+0 |
3.0 |
8.0 |
No
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Key Learning Outcomes of the Course Unit
On successful completion of this course unit, students/learners will or will be able to:
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PROGRAMME LEARNING OUTCOMES |
1 |
will learn the theory, history, mathematics and programming of evolutionary optimization algorithms
| 1 (5), 2 (3), 3 (3), 4 (4), 5 (4), 6 (4), 7 (4), 8 (3), 9 (3), 10 (3), 11 (4), 12 (3) | 2 |
will learn programming with genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization and convex optimization techniques
| 1 (5), 2 (3), 3 (3), 4 (4), 5 (5), 6 (4), 7 (4), 8 (3), 9 (5), 10 (3), 11 (5), 12 (3), 13 (5) | 3 |
Mathematics and science knowledge and understanding in engineering problems | 1 (5), 2 (3), 3 (3), 4 (4), 5 (4), 6 (4), 7 (4), 8 (3), 9 (3), 10 (3), 11 (4), 12 (3) | 4 |
Ability to analyze and interpret data on complex engineering systems in a multidisciplinary context.
| 1 (5), 2 (5), 3 (5), 4 (5), 5 (4), 6 (5), 7 (5), 8 (5), 9 (3), 10 (5), 11 (4), 12 (3) | 5 |
Ability to identify, formulate and solve unfamiliar complex engineering problems, to apply systems thinking in complex problem solving, to learn independently for life, undertake further work autonomously | 1 (5), 2 (3), 3 (3), 4 (4), 5 (4), 6 (4), 7 (4), 8 (3), 9 (3), 10 (3), 11 (4), 12 (3) | |