ECTS credits ECTS credits: 3
ECTS Hours Rules/Memories Hours of tutorials: 1 Expository Class: 10 Interactive Classroom: 11 Total: 22
Use languages English
Type: Ordinary subject Master’s Degree RD 1393/2007 - 822/2021
Departments: Electronics and Computing
Areas: Languages and Computer Systems
Center Higher Technical Engineering School
Call: Second Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
The main objective of this course is to learn and work on the processes involved in the management of artificial intelligence projects, taking into account both the software project management dimension and the particularities of artificial intelligence projects, with a comprehensive view of quality management that includes not only technical aspects but also ethical and legal aspects. Following this structure, the aim is to transmit and involve the students in all the necessary steps to obtain an artificial intelligence system from the point of view of project management, providing a global vision of the methodologies, processes and techniques for the development and management of intelligent systems. Students will be able to carry out the necessary activities for the planning and monitoring of a project in this field, both from the point of view of choosing activities, resources and technologies as well as the selection or design of the tools and variables for the correct evaluation and control of the results of all the phases of the project. In addition, basic knowledge will be provided on entrepreneurship based on Artificial Intelligence systems and applications and the business models involved, as well as the possibilities of financing such ventures. The different models of dissemination and diffusion of the results of AI projects will also be discussed.
Typology of projects and models in Artificial Intelligence.
Introduction to the development model in Machine Learning.
Development and management methodologies for Intelligent Systems.
Conception, preparation, and financing of R+D+i projects in AI.
Entrepreneurship concepts and their application in AI: business models and methodologies.
Publication of results and Open Science, Open Data, and society participation (RRI) movements.
Science dissemination and internationalization.
PMBOK: Guía de los Fundamentos Para la Dirección de Proyectos (guía del PMBOK)- 6 Ed, Project Management Institute, 2017. ISBN: 978-1628251944.
Scrum y XP desde las trincheras – 2ªEd, Henrik Kniberg, 2007. C4Media Inc. ISBN: 978-1-4303-2264-1
After taking the course the student should be able to see a software project as a set of processes. It is intended that the student acquires a vision of the scope involved in the development of a project, the processes involved and their necessity for the development of quality software.
As a result of the development of the course the students will acquire basic and general competences: CG1, CG2, CG4, CG5, CB6, CB7, CB9 and CB10. The transversal competences: CT5, CT8 and CT9 and the specific competences CE19, CE20, CE21, CE22, CE28 and CE29.
Expository method / master class: the teacher presents a topic to the students with the objective of providing a set of information with a concrete scope. information with a specific scope. This teaching methodology will be applied to the training activity "Theory classes".
Laboratory practices: the teacher of the subject presents the students with a problem or problems of a practical nature, the resolution of which requires the understanding and The resolution of these problems requires the understanding and application of the theoretical-practical contents included in the contents of the subject.
Students can work on the solution to the problems posed individually or in groups. This teaching methodology will be applied to the training activity "Practical laboratory classes" and can be applied to the training activity of "Problem-based learning sessions problem-based learning sessions, seminars, case studies and projects".
Project-based learning: students are given practical projects whose scope requires that a significant part of the student's total dedication to the subject be devoted to them. In addition, due to the scope of the work to be done, students are required to apply not only managerial skills but also technical skills.
In order to pass the subject, students must pass both the theory and the practice of the course separately. The practices are not recovered in July; except in those cases in which the student reaches 40% of the maximum grade of practices, allowing then to perform all the practices with respect to a new case study specifically raised for a possible recovery. In this case, the new practical case will be uploaded to the virtual platform two weeks before the theoretical exam of the course. In the evaluation of the work delivered by the students, the degree of achievement of the competences will be assessed, in particular the implementation of the contents provided by the course to these competences. In addition, the transversal competences will be assessed insofar as they are required for the development of these works.
The questions of the theoretical exam will focus on the specific contents, which have been developed in the subject, in relation to their competences and which may have been acquired both in the expository and interactive part. The average duration of the exam is approximately 2 hours and may consist of multiple-choice questions, short questions and case study problems. The exam will evaluate the degree of assimilation of the teaching objectives established in the syllabus of the subject.
There will be no partial exam.
Once both parts have been approved separately, each part will account for 50% of the final grade.
In order to receive a NO SHOW evaluation, one of the following circumstances must be present:
1. Not to have attended at least 85% of the practices of the subject.
2. Not having taken the theoretical exam of the subject in spite of having passed the practicals of the subject.
3. Not having taken the theoretical exam of the subject and having communicated explicitly and in writing to the person in charge of the subject that the subject is abandoned when, even having taken at least 80% of the practices of the subject, the practices of the subject have not been passed.
Weight of the continuous evaluation in the extraordinary opportunity of recovery (July tests):
1. The grade obtained in the practices during the course is maintained and also its weight in the final grade.
For cases of fraudulent performance of exercises or tests, the provisions of the Regulations for the evaluation of the academic performance of students and grade review will apply.
The total study time and the student's personal work is 75 hours, distributed approximately as follows:
1. Theory classes: 10 hours
2. Self-study of the student: 10 hours
3. Practical laboratory classes: 5 hours
4. Writing of practical work: 15 hours
5. Learning based on problems, case studies and projects: 6 hours.
6. Supervised assignments, exams, etc.: 29 hours.
The effort described between activities 4 and 6 can be reevaluated throughout the course without implying a total overexertion on the part of the student.
Official language of this subject, will be English
José Manuel Cotos Yáñez
Coordinador/a- Department
- Electronics and Computing
- Area
- Languages and Computer Systems
- Phone
- 881816461
- manel.cotos [at] usc.es
- Category
- Professor: University Lecturer
José Ángel Taboada González
- Department
- Electronics and Computing
- Area
- Languages and Computer Systems
- Phone
- 881816457
- joseangel.taboada [at] usc.es
- Category
- Professor: University Lecturer
| Monday | |||
|---|---|---|---|
| 17:00-18:30 | Grupo /CLE_01 | English | IA.02 |
| 18:30-20:00 | Grupo /CLIL_01 | English | IA.02 |
| 05.22.2025 16:00-20:00 | Grupo /CLIL_01 | IA.02 |
| 05.22.2025 16:00-20:00 | Grupo /CLE_01 | IA.02 |
| 06.27.2025 16:00-20:00 | Grupo /CLIL_01 | IA.02 |
| 06.27.2025 16:00-20:00 | Grupo /CLE_01 | IA.02 |