1. Understand the fundamental principles of artificial intelligence, and in particular generative artificial intelligence, and their relevance to teaching and scientific research;
2. Explore the various applications of generative artificial intelligence in teaching and research activities in different areas;
3. Acquire practical skills for integrating generative artificial intelligence tools into teaching and research activities;
4. Analyze the ethical and social possibilities and challenges associated with the use of generative artificial intelligence in the academic context;
5. Develop effective strategies for evaluating and validating the results obtained from the use of generative artificial intelligence in academic contexts.

1. Introduction to Artificial Intelligence, focusing on its definition, concepts, history and examples;
2. Introduction to Generative Artificial Intelligence, focusing on its definition, related concepts, origin and training of large language models, probability vs. factuality and limitations;
3. Use of Generative AI in Teaching and its application in lesson preparation, the classroom and assessment methods;
4. Use of Generative AI in Research and its application throughout the scientific method.

Participants will produce a report in which they apply the skills acquired on the course in one of two ways of their choice:
- Demonstration of how the tools can be used in a course they teach or a course of their choice;
- Demonstration of how the tools can be used in the development of an existing research topic or for the creation of a new research topic.