151818937 ARTIFICIAL INTELLIGENCE ( 3 Crd.Hrs )

The course is designed to prepare students to carry out in-depth research work, typically a thesis in an academic context or a research engineer's work in a professional context. At the end of the course, each student will have deepened a research sector in the field of Artificial Intelligence and will have consolidated the basic knowledge necessary for any Artificial Intelligence research. The course of Artificial Intelligence at doctoral level is thus organized according to the inverted class approach. The principle is the preparation of the courses by the students from the material made available. The teacher will discuss and propose the following main fields to students: • Knowledge engineering in the web era (information search, recommendations, social networks,...), • Collective intelligence (multi-agent) • Artificial intelligence for human learning • Learning Approaches for Artificial Agents • Artificial Intelligence and Data Sciences • Artificial intelligence and robotics • Artificial intelligence and connected objects • Other student-initiated topics. Course objectives Learning research in any field requires not only workload but also time to mature. The module requires a semester to be successfully completed by the students. Pedagogical appointments are important at the beginning and end of the semester, while progress monitoring is carried out remotely during the period of the research on the topic chosen by the students. The tentative timetable could be as follows: • 1 month of intensive training and situation studies. It concludes with a mini-course conducted by each student on the subject of their choice (inverted class). • 2 months of study with coaching and distance monitoring. • 1 month of intensive preparation for the presentation of the research work carried out. At the end of this period, a scientific seminar is organised as an international conference to present the work.