Teaching GuideTerm
Faculty of Computer Science
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Máster Universitario en Intelixencia Artificial
 Subjects
  Machine Learning II 
   Methodologies
Methodologies Description
Guest lecture / keynote speech The contents of the course will be taught indistinctly between lectures and interactive classes. The completion of all the proposed activities is necessary, as well as the attendance to all the classes (lectures and interactive) to pass the course.

Expository classes (theory): will consist of the explanation of the different sections of the course syllabus, with the help of electronic media (presentations, videos, etc.)
Seminar Case studies: students may be presented with real or fictional work scenarios that present certain problems. Students will have to apply the theoretical and practical knowledge of the subject to find a solution to the question or questions posed. As a general rule, case studies will be carried out in groups. The different working groups will present and share their solutions.
ICT practicals Interactive classes (practical): different practical problems related to the content of the subject will be posed for the student to solve individually or in groups.
Project-based learning: students may be given practical projects whose scope requires them to dedicate a significant part of their time to the subject.
Autonomous work: the scope and objectives of the projects, use cases and/or practical problems may require autonomous work on the part of the students, albeit under the supervision of the teaching staff.
Mixed objective/subjective test A mixed test which can contain quiz questions, short=answer questions or development questions. It is going to evaluate the teorethical part of the subject and it can contain questions about the content of the seminars or practical exercises
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