Introduction to algorithmic reasoning and structured programming using Python. Students learn about variables, control structures, functions, and problem decomposition through practical exercises inspired by CPGE concours problems.
Learning objectives: Develop precision in reasoning and mastery of algorithmic syntax.
Assessment: Quizzes, coding challenges, and graded notebook submissions.
Bridges mathematics and computer science by using Python to model physical or environmental systems. Ideal for MP/PSI students exploring applied scientific reasoning.
Learning objectives: Translate theoretical models into numerical simulations.
Assessment: Mini-projects with report and code validation.
Guidance for developing and presenting personal scientific projects (TIPE). Covers topic selection, experimental design, and clear scientific communication.
Learning objectives: Build autonomy, rigor, and clarity in scientific writing.
Assessment: Continuous supervision and oral presentation evaluation.