The course is structured around a programme of lectures delivered by internationally recognized specialists from different fields of genetics and the life sciences, including biomedicine, agrogenomics, microbiology, gene therapy, toxicology, genomics, and metagenomics, among others.

These lectures provide students with an overview of current applications of genetics in research, innovation, and knowledge transfer, while familiarizing them with major scientific and technological challenges in the field. The list of invited speakers and lecture titles will be announced through the Virtual Campus.

Attendance at all lectures is mandatory.

As part of the learning activities, students will compile an individual portfolio containing a summary and critical reflection on each lecture. Portfolio entries will be submitted periodically through the Virtual Campus and will constitute the evidence of learning for the course. The portfolio should demonstrate not only an understanding of the topics presented, but also the ability to analyse, synthesize, integrate knowledge, and critically reflect on the subjects discussed.

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.

Continuous assessment

Assessment is based on the continuous monitoring of the learning activities carried out throughout the course.

Attendance at all lectures is mandatory and constitutes an essential requirement for passing the course.

The individual portfolio will account for 100% of the final course grade.

Throughout the course, students are required to submit, via the Virtual Campus, a summary/critical reflection for each lecture. These submissions will together constitute the course portfolio.

The portfolio will be assessed according to the following criteria:

• understanding of the topics presented during the lectures;
• ability to analyse, synthesize, and critically reflect on the content;
• integration of the knowledge acquired with other concepts covered in the Master's programme and, where appropriate, with the relevant scientific literature;
• quality of written communication and appropriate use of scientific language;
• ability to identify the relevance and potential applications of the topics discussed.

A minimum final grade of 5 out of 10 is required to pass the course.

To be eligible for the resit assessment, students must have completed assessment activities representing at least two-thirds (67%) of the total course grade. Students whose completed assessment activities account for less than 67% of the final grade will receive the status "Not Assessed."

Students who are unable to submit one or more assessment activities for a duly justified reason and provide the appropriate supporting documentation must notify the teaching staff. In such cases, the teaching staff will determine the most appropriate alternative assessment procedure.

Single assessment

Students opting for the single assessment system must submit a complete portfolio containing the summaries/critical reflections corresponding to all lectures delivered throughout the course.

The portfolio will account for 100% of the final course grade and will be assessed using the same criteria as those applied in the continuous assessment system. It must be submitted on the date established for the single assessment according to the academic calendar.

The same resit regulations that apply to continuous assessment will also apply to the single assessment.

Use of Artificial Intelligence

The use of Artificial Intelligence (AI) technologies is permitted in this course only as a support tool, for example for literature or information searches, language editing, or translation.

Students must clearly acknowledge any use of AI tools by identifying the sections of the work that have been assisted or generated using AI, specifying the tools used, and providing a brief critical reflection on how these tools contributed to the development of the work.

Failure to disclose the use of AI will be considered a breach of academic integrity and may result in a partial or total loss of marks for the assessment, as well as more severe disciplinary sanctions where appropriate.

Any irregularity committed during an assessment activity (including academic fraud, plagiarism, or the improper use of AI, unless such use is expressly authorized in the course syllabus) that may lead to a significant alteration of the assessment outcome will result in a grade of 0 for that assessment activity. If the course syllabus establishes that obtaining a minimum grade in that assessment activity is a compulsory requirement for passing the course, or if multiple irregularities occur in the assessment activities of the same course, the final grade for the course will be 0. In addition, disciplinary proceedings may be initiated against any student who commits any of these irregularities.