Objectives of Programme's Learning Outcomes

• Imagine, design, develop, and implement conceptual models and computer solutions to address complex problems including decision-making, optimisation, management and production as part of a business innovation approach by integrating changing needs, contexts and issues (technical, economic, societal, ethical and environmental).
• On the basis of modelling, design a system or a strategy addressing the problem raised; evaluate them in light of various parameters of the specifications.
• Evaluate the approach and results for their adaptation (modularity, optimisation, quality, robustness, reliability, upgradeability, etc.).
• Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out computer and management engineering missions, using their expertise and adaptability.
• Master and appropriately mobilise knowledge, models, methods and techniques specific to computer management engineering.
• Identify and discuss possible applications of new and emerging technologies in the field of information technology and sciences and quantifying and qualifying business management.
• Assess the validity of models and results in view of the state of science and characteristics of the problem.
• 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
• 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.
• Use and produce scientific and technical documents (reports, plans, specifications) adapted to the intended purpose and the relevant public.
• Adopt a professional and responsible approach, showing an open and critical mind in an independent professional development process.
• Exploit the different means available in order to inform and train independently.
• 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.

Learning Outcomes of UE

Get familiar with the contemporary methods in machine learning (active learning, reinforcement learning, depp networks)
Study these methods within the frameworks of statistical learning theory      

 

UE Content: description and pedagogical relevance

active learning, reinforcement learning, deep networks, statistical learning theory

Prior Experience

basic knowledge in data mining / machine learning
python programming
mathematical bases