Objectives of Programme's Learning Outcomes

• Plan, manage and lead projects in view of their objectives, resources and constraints, ensuring the quality of activities and deliverables.
• Define and align the project in view of its objectives, resources and constraints.
• Assess the approach and achievements, regulate them in view of the observations and feedback received.
• Respect deadlines and timescales
• Work effectively in teams, develop leadership, and make decisions in multidisciplinary, multicultural and international contexts.
• Interact effectively with others to carry out common projects in various contexts (multidisciplinary, multicultural, and international).
• Contribute to the management and coordination of a team that may be composed of people of different levels and disciplines.
• Communicate and exchange information in a structured way - orally, graphically and in writing, in French and in one or more other languages - scientifically, culturally, technically and interpersonally, by adapting to the intended purpose and the relevant public.
• Argue to and persuade customers, teachers and boards, both orally and in writing.
• Select and use the written and oral communication methods and materials adapted to the intended purpose and the relevant public.
• Use and produce scientific and technical documents (reports, plans, specifications) adapted to the intended purpose and the relevant public.
• Contribute by researching the innovative solution of a problem in engineering sciences.
• Construct a theoretical or conceptual reference framework, formulate innovative solutions from the analysis of scientific literature, particularly in new or emerging disciplines.
• Develop and implement conceptual analysis, numerical modelling, software implementations, experimental studies and behavioural analysis.
• Collect and analyse data rigorously.

Learning Outcomes of UE

Keras (python) framework for training DNNs Deep reinforcment learning SLAM (Simultaneous localizatino and mapping) for automatic cartography

UE Content: description and pedagogical relevance

Three challenges to discover the tools of AI

Prior Experience

Practical knowledge of a programming language (preferably python)