Degree | Type | Year |
---|---|---|
Research and Innovation in Computer based Science and Engineering | OP | 1 |
You can view this information at the end of this document.
There are no formal prerequisites. Graduate-level knowledge on topics related to data transmission are assumed.
The objective of this course is to study and delve into different data transmission search topics. To do this, the course focuses on providing an introduction to research in three main blocks:
Students will learn advanced concepts of these topics and will be introduced to current research.
The main contents of the course are divided into the three main blocks of the subject:
Depending on the background and interests of the students, they will have the opportunity to delve more or less into certain topics.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Preparation of written assignments | 25 | 1 | CA12, CA13, SA22, SA23, CA12 |
Study for tests and presentations | 15 | 0.6 | KA16, KA17, KA18, KA16 |
Teacher directed sessions | 45 | 1.8 | KA16, KA17, KA18, SA21, SA22, KA16 |
Type: Supervised | |||
In-class activites | 15 | 0.6 | SA21, SA22, SA23, SA21 |
Type: Autonomous | |||
Homework and class preparation | 35 | 1.4 | KA16, KA17, KA18, SA21, KA16 |
Preparation of synthesis tests | 15 | 0.6 | CA12, CA13, SA21, SA22, SA23, CA12 |
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.
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.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Assignments | 70% | 0 | 0 | CA12, CA13, SA22, SA23 |
Synthesis test | 30% | 0 | 0 | KA16, KA17, KA18, SA21, SA22, SA23 |
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:
The assessment activities will be explained in detail at the beginning of the course.
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.
Will be provided at the beginning of the course. Given the dynamic nature of the topics to be presented, the specific bibliography will change each course to adapt it to the current state-of-the-art research in this area. It will usually include relevant papers.
Will be provided at the beginning of the course.
Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PLABm) Practical laboratories (master) | 1 | English | second semester | morning-mixed |
(TEm) Theory (master) | 1 | English | second semester | morning-mixed |