Teaching GuideTerm Faculty of Computer Science |
Grao en Intelixencia Artificial |
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Identifying Data | 2023/24 | |||||||||||||
Subject | Fundamentals of Machine Learning | Code | 614G03018 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Graduate | 2nd four-month period |
Second | Obligatory | 6 | ||||||||||
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Methodologies | Competencies | Description | Qualification |
Laboratory practice | A1 A2 B3 B7 C3 | Development of a Machine Learning system based on explanations made in theory. | 25 |
Supervised projects | A1 A2 A15 B3 B7 B10 | Writing of the report on the resolution of the real problem carried out in the laboratory practices. The writing of the report will include a bibliographic review of the most important works related, written in English for the most part, documentation on the problem to be solved, methodology used, and comparison of the results found in the application of the different techniques, as well as a critical evaluation of both the results obtained and the information used. | 25 |
Objective test | A1 A12 B5 B7 B10 | Test questions about the contents of the course, based on the different machine learning techniques and their applications. | 50 |
Assessment comments | |||
In order to pass the subject, the student must obtain a minimumscore of 5 out of 10 in the result of combining the grades of the objectivetest, the laboratory practices and the supervised works. In addition, thestudent must obtain a minimum score of 2 out of 5 points in the objective test.If the student does not obtain this minimum grade, the grade of the subjectwill be that corresponding to the grade of the objective test. In the second opportunity, the grade obtained in the laboratory practices and supervised works will be maintained, not being able to obtain again a grade since it results from the continuous evaluation of the workduring the credits of practice of the subject. The student can retake the examination of the objective test, the criteria for obtaining the total scorebeing those indicated at the beginning of this section. Part-time students must deliver in their reports on the same dates as full-time students, and attend the RGTs in which they will be corrected. Similarly, it is recommended that they attend the practice classes. No-show qualification: The student will receive the qualification of "no-show" when he/she does not take the final exam. Fraudulent performance of exercises or tests: The fraudulent execution of tests or assessment activities, once proven, will result in a direct failing grade in the examination in which it was committed. The student will be given a grade of "suspenso" (numeric grade 0) in the corresponding academic year's examination, whether the offense occurs in the first opportunity or the second. In order to do so, the student's grade will be modified in the first opportunity's record, if necessary. |
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