The methodology of this course is designed to expose students to some of the relevant research topics in the areas of coding theory, computer networks and security. It will be based on the concept of \"learning by doing\", and will be adapted to the number of students who enroll in the course. There will generally be a combination of theoretical and practical sessions, including lectures, student assignments, presentations, challenge solving, and collaborative work.

We want to adopt an assessment methodology that is flexible enough to adapt to the specific work done in class, which means that it can vary slightly from one course to another. The evaluation will be based on 2 different types of activities:

• Assignments: different assignments will be proposed to students during the course. These may include individual and group work and may have a theoretical or practical orientation. Examples can be: exercises, study and presentation of a topic related to the subject, challenge based learning activities, practices, ...
• Tests: Summative tests will be used as an individual assessment activity. These tests can be replaced by other assessment activities if, for example, the number of students is low. The minimum mark required for this part is 4 out of 10.

The assessment activities will be explained in detail at the beginning of the course.

The minimum mark required to pass the course is 5 out of 10 points. "Honours Distinction" (Matrícula d’Honor) will be awarded taking into account the results achieved on synthesis tests, as well as active participation throughout the course and the quality of the assignments.

Only students who have not participated in any assessment activity will receive the grade Not Assessed.

Use of Generative AI Tools

This course acknowledges the growing use of generative artificial intelligence as a support tool and therefore allows its use in a limited manner. In general, these tools may only be used to improve formal aspects of the work, such as writing, style, clarity of exposition, linguistic correctness, or translation, as well as for occasional assistance with technical aspects.

It is not acceptable to use generative artificial intelligence tools to generate content that is subject to assessment, such as methodological approaches, designs, experiment execution, analysis or interpretation of results, idea development, or conclusion formulation. These tasks must be carried out entirely by the student, as they represent the core intellectual and creative work required to pass the course. Given the wide variety of assignments, please consult your tutor if in doubt.

In any case, students must explicitly state, in each report or deliverable, whether generative AI tools have been used, specifying which tools were employed, for what purpose, and to what extent. Irresponsible, excessive, or unnecessary use of these tools may negatively affect the final grade of the bachelor's thesis. Undeclared or improper use of such tools may result in failing the course.