The development of the course, in terms of teaching methodology and training activities, is based on the following activities:

- Lectures/flipped classroom, where students acquire the theoretical knowledge of the subject.

- Seminars, which are sessions with a small number of students that should serve both to answer questions and to study more deeply certain key concepts and their application in practical cases. They are mostly dedicated to solve exercises.

- Evidences, which are exercises solved individually in or outside the master classes.

For this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively in study support tasks, such as bibliographic or information searches outside the classroom. In any case, the student must clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how these have influenced the process and the final result of the activity/study. The lack of transparency in the use of AI in these activities will be considered a lack of academic honesty and may lead to a partial or total penalty in the grade of the activity, or greater sanctions in serious cases.

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

The evaluation of the scientific-technical knowledge of the subject achieved by the student, is done individually, continuously and through written tests consisting of:

- 2 partial exams with an incidence in the final mark of 40% the first and of 45% the second. The minimum grade required to pass the course is 4.0 out of 10.0 in each exam.

- Resolution of exercises (evidences) with an overall incidence of 15%. These exercises are compulsory and thus, those students who fail to do so will automatically be graded with a zero.

- For students who have not passed one of the partial exams there will be a retake of one or both partial exams.

- The student who has passed the exams may decide to take the retake to improve the mark, with the understanding that the student will give up the grade achieved in the first place.

- To pass the subject, a minimum of 5.0 points out of 10.0 calculated according to the percentages given above.

- A student is graded as “non-assessable” if she/he has participated in assessment activities that represent ≤ 15% of the final grade.

Single assessment will consist of a single test in which the contents of the entire subject program will be assessed with different types of exercices (multiple-choice test, problem solving, development of concepts, etc.) The grade obtained in this test will account for 100% of the final grade and the minimum grad to pass the subject is a 5.0 out of 10.0 for the single test. The single assessment test will take place on the same day, time and place as the last continuous assessment test of the subject. The single assessment can be recovered on the day set for the recovery of the subject. A student is graded as “non-assessable” applying the same criterion as for continuous assessment. The review of the final grade follows the same procedure as for continuous assessment.

The use of Artificial Intelligence (AI) technologies is not permitted in any assessment activity within the classroom, including midterm exams and evidence. The lack of transparency in the use of AI in assessable activities will be considered a lack of academic honesty and may result in a partial or total penalty in the grade of the activity, or greater sanctions in serious cases.