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Teaching GuideTerm Escola Politécnica de Enxeñaría de Ferrol |
Guía Provisional
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| Mestrado Universitario en Enxeñaría Industrial (plan 2018) |
 Subjects |
| Introduction to Machine Learning |
| Assessment |
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| Identifying Data | 2024/25 | |||||||||||||
| Subject | Introduction to Machine Learning | Code | 730497240 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
Second | Optional | 4.5 | ||||||||||
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| Methodologies | Competencies / Results | Description | Qualification |
| Oral presentation | B1 B5 B15 B14 B6 C7 C9 C11 | The oral presentation, the participation in the discussion and the written inform will be considered in the final qualification. It is mandatory to pass this methodology independently in order to pass the whole subject. | 30 |
| Supervised projects | B2 B3 B4 B13 C1 C3 | Different programming projects will be proposed along the course that must be carried out in an autonomous way by the student and that will be presented and explained to the teachers afterwards. It is mandatory to pass this methodology independently in order to pass the whole subject. | 60 |
| Document analysis | B3 B5 B14 B6 C11 | Part of the lectures will be used to evaluate the understanding of the documentary sources, which will be provided by the teachers prior to the class for consultation and understanding. These evaluations will be carried out by means of group work, small reports, questionnaires, or other methodologies that allow an objective assessment of the degree of analysis carried out. | 10 |
| Assessment comments | |||
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First opportunity: To pass the course on the first opportunity, a minimum score of 50 must be achieved by adding up all the previous methodologies, being necessary to obtain a minimum of 30 in the Supervised Work and 20 in the sum of the Oral Presentation and the Analysis of documentary sources. Second opportunity: If the student does not pass the subject on the first opportunity, he/she must repeat the activities that are necessary from the method(s) that were not passed in the second call. For example, if a student passed the Oral Presentation + Analysis of documentary sources part, but failed the Supervised Work, he/she must repeat the practical work necessary to pass the course, normally those that were not individually passed. In the second opportunity, the minimum grade criteria established in the first call are maintained. Early opportunity For this opportunity, the same criteria are maintained as for the first, with the student having to specify delivery deadlines with the subject teachers. Students with part-time registration or academic exemption They may accumulate 15% of the grade corresponding to the Analysis of documentary sources in the oral presentation in the both opportunities. This modification must be requested from the professors of the subject at the beginning of the semester. Likewise, if they cannot make the oral presentation with the rest of the students, they must arrange an alternative date with the professors in all sessions. All regulatory aspects related to “academic exemption”, “dedication to study”, “permanence” and “academic fraud” will be governed in accordance with the current academic regulations of the UDC (https://www.udc.es/es/normativa/academica/) |
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