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COMPUTER ENGINEERING (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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INTRODUCTION TO MACHINE LEARNING |
TEL419 |
4 |
8 |
3+0 |
3.0 |
6.0 |
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 |
To learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. | 2 (5), 3 (5), 4 (5), 5 (5), 6 (5), 7 (5), 8 (5), 9 (5), 12 (5), 13 (5), 14 (5), 15 (5), 16 (5) | 2 |
understanding, techniques, and algorithms in machine learning, on applications and gaining practice | 2 (5), 3 (5), 4 (5), 5 (5), 6 (5), 7 (5), 8 (5), 9 (5), 12 (5), 13 (5), 14 (5), 15 (5), 16 (5) | 3 |
practicing on topics such as classification and linear regression and more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. | 2 (5), 3 (5), 4 (5), 5 (5), 6 (5), 7 (5), 8 (5), 9 (5), 12 (5), 13 (5), 14 (5), 15 (5), 16 (5) | |