Entry points, 1st year, Common Courses
Academic year 2025/2026
| Module | Description | ECTS |
| Artificial Intelligence & Computer Science Core | All entry universities will be offering courses in Artificial Intelligence and Computer Science, covering the fundamentals of programming and mathematics required for AI, as well as a strong base in Artificial Intelligence methods. | Between 20-25 ECTS |
| Emotional AI Core | All entry universities will be offering courses covering the Emotional Artificial Intelligence. | Between 11-16 ECTS |
| Innovation and Entrepreneurship | All entry universities will be offering courses on idea generation, technology-based entrepreneurship, marketing and markets, organization and project management, new product and process development, entrepreneurial finance, human resource development | 24 ECTS (including summer school) |
Entry Universities
- Eötvös Loránd University (ELTE) – Hungary
- Politecnico di Milano (POLIMI) – Italy
- Université Côte d'Azur (UCA) – France
- University of Trento (UNITN) – Italy
- Universidad Politécnica de Madrid (UPM) – Spain
- University of Rennes (UR) – France
- University of Turku (UTU) – Finland
Artificial Intelligence & Computer Science Core
- Mathematics and Computing - To describe and explain the general mathematical and computing principles, specific tools, traditional and novel methods of artificial intelligence. Practical aspects and relevant implementation will be presented using the latest technical tools.
- Machine Learning - To describe and explain fundamentals of machine learning and the classical concepts for algorithm training. Also be able to apply machine learning approaches to solve simple problems on small datasets.
- Deep Learning - To describe and explain the theoretical basics of Deep Learning. Also be able to apply deep learning approaches to solve simple problems on small datasets.
- Software Tools - To describe and explain AI software languages and formulation of the algorithms. Be able to use state-of-the-art/most recent deep learning framework and an open-source neural network software to solve demonstrative problems on small datasets.
- Data Representation and Processing / Symbolic AI - To describe and explain general theories and concepts related to knowledge representation, to prepare, pre-process and analyse different types of data before applying any AI approach to solve problems. Be aware of common data format and quality issues and be able to solve them and adapt this knowledge to the task.
- Ethical, Privacy and Security - Aspects To understand the complex ethical considerations of AI and the special privacy and security related aspects of its development and application.
Emotional AI Core
- Human Perception - To understand human cognitive and perceptual functions in order to provide a basis for further analysis of human intentions, cognitive control, social behavior, language, memory, Emotionals and general perceptions.
- Embodied AI - To recognize, correctly interpret, express and match the intentions of the human partner and the embodied AI (for example a robot), and to understand the methodological possibilities of interaction in the field of collaborative robot technology. Practical aspects and relevant implementation will be presented using the latest technical tools.
- Emotional/Modalities - To describe and explain the theoretical methods, designs, traditional and novel applications/tools for interpreting people's Emotionalal states from one main modality and optionally from more modalities. Additionally, to apply small practical demonstrations for solving simple, related tasks.
- Natural Language Processing - To describe and explain fundamentals of specific tools and methods of Natural Language Processing and Language-based Foundation Models.
Exit points, 2nd year, Specialisation
Academic year 2026/2027
| Module | Description | ECTS |
| Emotional AI Specializations | Students to select their specialization topic in Emotionalal Artificial Intelligence. | Between 20-25 ECTS |
| Masters’ Thesis | Students to complete their Masters’ Thesis | 30 ECTS |
| I&E Study Course | Supervised business analysis work that focuses on applying prior I&E knowledge and competencies in a real business context. This is a chance to tackle an actual business challenge using a robust, explorative business analysis methodology. | 6 ECTS |
Eötvös Loránd University (ELTE)
Specialization: Humane Aspects of Applied Emotionalal AI
To explore and understand the broad dimension of new techniques and applications supported by Emotionalal AI, focusing on human intention and the expression of Emotional through different modalities, together with critical thinking and general ethical considerations.
EURECOM
Specialization: Emotionalal AI embodied in Multimodal Agents
Design, development and deployment of Emotionalal AI in Multimodal Agents. Multimedia analysis (face recognition, facial beauty assessment, sound processing, sentiment analysis). Neuro-symbolic systems. Conversational assistants with Emotionalal roles. Bias, fairness and ethical aspects of Emotional AI.
Technical University of Madrid (UPM)
Specialization: Practical Emotionalal AI: healthcare
Design and deployment Emotionalal AI solutions in practice. Usage of cloud resources, integration of different devices and systems with its application to healthcare.
Université Côte d’Azur (UCA)
Specialization: Holisitic interdisciplinary aspects
To understand the multifaceted domain of Emotionals, from signal processing and machine learning dimensions of Emotional capture, to psychological, behavioral, societal, and ethical aspects.
University of Trento (UNITN)
Specialization: Emotionalal AI in Robotic Applications
Design, development and implementation of Emotionalally intelligent AI equipped robotic systems for multifaced domain applications. Acquire expertise in design, development and implementation of advanced human computer interaction going beyond the interaction paradigms traditionally adopted in Human Computer Interaction, interactive multisensory networked systems, collaborative Emotionalally intelligent or emphatic robotic systems. Methods and means for developing Emotionalally intelligent systems in different contexts.
University of Turku (UTU)
Specialization: Emotionalal AI in healthcare and medicine
Emotionalal AI in healthcare and medicine: Design, development, and implementation of Emotionalally intelligent AI systems for healthcare applications. Gamification strategies for designing interactive healthcare solutions that enhance patient engagement and Emotionalal well-being. Methods and means for evaluating the effectiveness of these systems in appropriate contexts.
