The following table shows a general picture of the syllabus by its temporal distribution organised in quadrimesters and, inside them, bimesters. Courses colored in pink are compulsory whereas those colored in blue are elective. A darker color means that the course has a work load of 6 ECTS credits whereas light colors mean 3 ECTS. As you can see, there are some elective courses that last two months but have a load of 6 ECTS.
Q1: First year, September to December
The first quadrimester consists of 7 compulsory courses. Three of them are taught during the whole quadrimester:
| Acronym / teaching guide | Name | Period | Type | ECTS | Head professor |
| RP [guide] | Reasoning and Planning | Q1 | Compulsory | 6 | Pedro Cabalar (UDC) |
| NLU [guide] | Natural Language Understanding | Q1 | Compulsory | 6 | Carlos Gómez (UDC) |
| ML1 [guide] | Machine Learning I | Q1 | Compulsory | 6 | Enrique Fernández Blanco (UDC) |
| AIF [guide] | AI Fundamentals | Q1-1 | Compulsory | 3 | David Chaves (USC) |
| DE [guide] | Data Engineering | Q1-1 | Compulsory | 3 | Anália Lourenço (UVigo) |
| CV1 [guide] | Computer Vision I | Q1-2 | Compulsory | 3 | Xosé Manuel Pardo (USC) |
| IR1 [guide] | Intelligent Robotics I | Q1-2 | Compulsory | 3 | Fran Bellas (UDC) |
Q2: First year, mid January to mid May
The second quadrimester comprises two small compulsory courses of 3 ECTS each and a wide umbrella of elective courses of different sizes and durations
| Acronym / teaching guide | Name | Period | Type | ECTS | Head Professor |
| DL [guide] | Deep Learning | Q2 | Elective | 6 | Eduardo Mosqueira (UDC) |
| TXAI [guide] | Trustworthy and Explainable AI | Q2-1 | Compulsory | 3 | José María Alonso (USC) |
| AIPM [guide] | AI Project Management | Q2-1 | Compulsory | 3 | José Manuel Cotos (USC) |
| ML2 [guide] | Machine Learning II | Q2-1 | Elective | 3 | David Mera (USC) |
| MAS [guide] | Multiagent Systems | Q2-1 | Elective | 6 | Noelia Sánchez (UDC) |
| KRU [guide] | Knowledge Representation with Uncertainty | Q2-1 | Elective | 3 | Alberto Bugarín (USC) |
| EC [guide] | Evolutionary Computation | Q2-1 | Elective | 3 | Arno Formella (UVigo) |
| CV2 [guide] | Computer Vision II | Q2-2 | Elective | 6 | Noelia Barreira (UDC) |
| IR2 [guide] | Intelligent Robotics II | Q2-2 | Elective | 6 | Richard Duro (UDC) |
| LM [guide] | Language Modelling | Q2-2 | Elective | 3 | Pablo Gamallo (USC) |
| WIST [guide] | Web Intelligence and Semantic Technologies | Q2-2 | Elective | 6 | María Jesús Taboada (USC) |
| PM [guide] | Process Mining | Q2-2 | Elective | 3 | Manuel Lama (USC) |
| IRTS [guide] | Intelligent Real Time Systems | Q2-2 | Elective | 3 | Juan Carlos González (UVigo) |
Q3: Second year, September to December
The last quadrimester is not divided into bimesters and consists of 7 elective courses plus work placement and a final MSc Thesis.
| Acronym /teaching guide | Name | Period | Type | ECTS | Head Professor |
| WP | Work Placement (Internships) | Q3 | Compulsory | 6 | local in each univ. |
| MT | Master Thesis | Q3 | Compulsory | 12 | local in each univ. |
| COG [guide] | Computational Aspects of Cognitive Systems | Q3 | Elective | 3 | Ana B. Porto (UDC) |
| TM [guide] | Text Mining | Q3 | Elective | 3 | Francisco José Ribadas (UVigo) |
| BDE [guide] | AI in Big Data Environments | Q3 | Elective | 6 | Verónica Bolón (UDC) |
| IOT [guide] | Intelligent IoT | Q3 | Elective | 3 | Paula López (USC) |
| CYB [guide] | Intelligent Cybersecurity | Q3 | Elective | 3 | Francisco José Ribadas (UVigo) |
| EEAI [guide] | Emerging and Entrepreneurial AI | Q3 | Elective | 3 | Senén Barro (USC) |
| AIH [guide] | AI in Health | Q3 | Elective | 3 | Alejandro Pazos (UDC) |