Degree | Type | Year |
---|---|---|
Artificial Intelligence | OB | 4 |
You can view this information at the end of this document.
No prerequisites have been defined.
This subject aims to provide the student with a broad vision of the main challenges and applications of artificial intelligence (AI) in different fields of application.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Theory classes | 12 | 0.48 | 7, 6 |
Type: Supervised | |||
Project follow-up | 10 | 0.4 | 1, 3, 7, 6, 10 |
Type: Autonomous | |||
Work in the project | 114 | 4.56 | 1, 2, 4, 3, 7, 6, 8, 10, 5 |
The course will be organised around the development of a practical project based on a real use case of AI in one of the application areas covered in the module. At the beginning of the module, the challenges, opportunities and potential issues arising from the use of AI in each area will be presented. Based on this introduction, various use cases will be defined, and students will work in small groups of 4 to 6 people to analyse the case and propose alternative solutions.
Class activities will be organised into two types of sessions:
Students will be expected to build on the work done in face-to-face sessions with their own independent study in order to complete the project. The bulk of the work required for the project must be carried out independently, outside scheduled class time.
All information related to the module and any necessary documentation will be available on the virtual campus (cv.uab.cat).
On the first day of the course, a detailed calendar with the content of each session will be presented. This will be made available on the course’s virtual campus, where students will find all the learning materials and information needed to follow the course effectively. In the event that the teaching modality is modified due to force majeure as determined by the relevant authorities, the teaching staff will inform students of any changes to the course schedule and teaching methods.
Notes
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 |
---|---|---|---|---|
Oral presentation | 20% | 2 | 0.08 | 4, 3, 8 |
Project follow-up | 20% | 2 | 0.08 | 1, 2, 4, 3, 7, 6, 8, 9, 10, 11, 5 |
Written report | 20% | 10 | 0.4 | 1, 2, 4, 3, 7, 6, 9, 5 |
Evaluation activities consist of several components. The final project grade is calculated by weighting the evidence collected from each of the following activities:
In the event that the student commits any irregularity that could lead to a significant alteration of the mark of an assessment activity, that assessment activity will be awarded a mark of 0, regardless of any disciplinary proceedings that may be initiated. If multiple irregularities occur in the assessment activities of the same subject, the final mark for that subject will be 0.
This course does not provide for a single-assessment system.
In this course, the use of Artificial Intelligence (AI) technologies is permitted as an integral part of assignment development, provided that the final outcomedemonstrates a significant contribution from the student in terms of analysis and personal reflection. Students must clearly identify any content generated using AI, specify the tools employed, and include a critical reflection on how these technologies have influenced both the process and the final result of the assignment. Failure to disclose the use of AI in this assessed activity will be considered a breach of academic integrity and may result in a partial or total penalty to the assignmentgrade, or more serious sanctions in severe cases.
Bibliography
Dodhia, R. (2024). AI for social good: Using artificial intelligence to save the world. John Wiley & Sons.
Russell, S. J., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.
Sutherland, K. E. (2025). Artificial Intelligence for Strategic Communication. Springer Books.
Chemnad K and Othman A (2024). Digital accessibility in the era of artificial intelligence—Bibliometric analysis and systematic review. Front. Artif. Intell. 7:1349668. doi: 10.3389/frai.2024.1349668
* Additional detailed bibliography will be provided during the sessions.
Not defined
No specific software is needed
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 |
---|---|---|---|---|
(PAUL) Classroom practices | 711 | English | first semester | afternoon |
(TE) Theory | 71 | English | first semester | afternoon |