Objectives of Programme's Learning Outcomes

• Imagine, design, build and operate machines, equipment and processes to provide a solution to a complex problem of energy production, conversion and transmission by integrating the needs, constraints, context and technical, economic, societal, ethical and environmental issues.
• Identify the complex problem to be solved and develop the specifications by integrating the needs, constraints, context and technical, economic, societal, ethical and environmental issues.
• Implement a chosen solution in the form of a drawing, schematic, diagram or plan that conforms to standards, a model, a prototype, software and/or a digital model.
• Evaluate the approach and results in order to adapt or optimize the proposed solution.
• Mobilize a structured set of scientific knowledge and skills and specialized techniques to meet, with expertise and adaptability, the missions of the civil engineer in energy engineering.
• Master and appropriately mobilize knowledge, models, methods and techniques related to solid and fluid mechanics, energy exchange, dynamic and vibratory behavior of systems, mechanical manufacturing and production, machine operation, physical phenomena, machines, equipment and processes related to the production, conversion and transmission of energy
• Assess the validity of models and results given the state of the science and the characteristics of the problem.
• Work effectively in a team, develop leadership, make decisions in multidisciplinary, multicultural and international contexts.
• Interact effectively with other actors to carry out joint projects in various contexts (multidisciplinary, multicultural and international).
• Contribute to the management and coordination of a team that may be composed of people from different levels and disciplines.
• Identify skills and resources, and seek external expertise if necessary.
• Communicate and exchange information in a structured manner - orally, graphically and in writing, in French and in one or more other languages - at the scientific, cultural, technical and interpersonal levels, adapting to the goal pursued and the audience concerned.
• Use and produce scientific and technical documents (report, plan, specifications, ...) adapted to the goal and the public concerned.
• Act as a responsible, open-minded, and critical professional in an autonomous professional development process.
• Make critical use of the various means available for independent research and training.

Learning Outcomes of UE

Practical (hands-on) knowledge of the AI tools (mostly deep nets and deep reinforcement learning); knowledge og the state-of-the-art deep net architectures for solving AI problems.

UE Content: description and pedagogical relevance

Three applicative challenges in AI, coming from various domains are proposed. For each challenge, 3 hours are devoted to theory, followed by two 3-hours co-working sessions in teams, and a report is prepared by students at home.
A series of seminars are organized in parallel, on transdisciplinary topics related to AI. 
All activities are proposed in evenings (in the same format as the Mons AI Meetups launched in 2017).
They are also accessible to people registered to the Certificat d'Université en Intelligence Artificielle (See this page for more info, especially the Programme and Structure tab)  

Prior Experience

Basics of computer science and programming languages (Python)