Teaching GuideTerm
Faculty of Computer Science
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Máster Universitario en Intelixencia Artificial
 Subjects
  AI Fundamentals
   Assessment
Methodologies Competencies Description Qualification
Guest lecture / keynote speech A5 A17 B1 B2 B3 B4 B5 B6 B7 B8 C2 C3 C4 C6 C7 C8 C9 Exame escrita para evaluar os coñecementos da Materia 50
Laboratory practice A5 A17 B1 B2 B3 B4 B5 B6 B7 B8 C2 C3 C4 C6 C7 C8 C9 Evaluación de traballos prácticos 50
 
Assessment comments

The learning assessment considers both the theoretical and the practical part. In order to pass the subject an overall mark equal to or higher than 5 must be obtained, out of a maximum of 10 points in the assessment activities, whose weight in the final assessment will be within the ranges included in the degree report:

E1: Final exam 50%

E2: Evaluation of practical work 50%.

Students who have not taken the exam and have not submitted to the evaluation of any other compulsory activity will obtain the grade of not presented.

In order to pass the course in the second opportunity, students must submit to the evaluation of all those parts or pending compulsory deliveries that are established. For the rest, the grades obtained during the course will be retained

The fraudulent performance of tests or assessment activities, once verified, will directly involve disqualification in the call in which it is committed: the student will be qualified with numerical grade 0 in the corresponding call of the academic year, both if fraud is committed in the first opportunity as in the second. For this, qualification will be modified in the first opportunity report, if necessary

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