Objectives of Programme's Learning Outcomes

• Implement an engineering approach dealing with a set problem taking into account technical, economic and environmental constraints
• Design, evaluate and optimise solutions addressing the problem
• Implement a chosen solution in the form of a drawing, a schema, a plan, a model, a prototype, software and/or digital model
• Identify and acquire the information and skills needed to solve the problem
• Understand the theoretical and methodological fundamentals in science and engineering to solve problems involving these disciplines
• Select and rigorously apply knowledge, tools and methods in sciences and engineering to solve problems involving these disciplines
• Collaborate, work in a team
• Interact effectively with other students to carry out collaborative projects.
• Communicate in a structured way - both orally and in writing, in French and English - giving clear, accurate, reasoned information
• Argue to and persuade customers, teachers and a board both orally and in writing
• Demonstrate thoroughness and independence throughout their studies
• Identify the different fields and participants in engineering
• Demonstrate self-awareness, asses themself, and develop appropriate learning strategies.
• Direct their choice of modules within their degree programme in order to develop a career plan in line with the realities in the field and their profile (aspirations, strengths, weaknesses, etc.)
• Develop their scientific curiosity and open-mindedness
• Learn to use various resources made available to inform and train independently

Learning Outcomes of UE

acquire algorithmic knowledge and specific programming skills in order to be able to solve engineering problems in a limited time and participate in external challenges
Attendance at theory/exercises classes of at least 80% is required. Attendance at practical sessions (and challenges) and seminars is mandatory.

UE Content: description and pedagogical relevance

- Algorithmic part: greedy algorithms, graph problems, computational geometry, etc.
- Implementation part: advantages / disadvantages of programming languages according to usage, read / write input/output files, hash table, data structure, etc.
We will approach these lessons in parallel with the statements of previous competitions

Attendance at theory/exercises classes of at least 80% is required. Attendance at practical sessions (and challenges) and seminars is mandatory.

The teaching methods are likely to be adjusted according to the context imposed by the health measures.

Prior Experience

mathematics and computer science courses of the first two blocks