Foundations of Programming and Scientific Computing with Python

Brief description

This course introduces the foundations of programming and scientific computing using Python. Students will learn how to set up a Python working environment (local and cloud), write correct and readable programs using core syntax (data types, operators, control flow), and apply programming to mathematical problems. The course progressively prepares students for scientific computing tasks such as numerical experiments, data processing, and visualization using standard scientific tools.

Target audience

  • First-year undergraduate students (Licence 1) in Mathematics

General objectives

By the end of the course, students will be able to:

  • Install and configure a Python environment (Anaconda/pip) and work efficiently with Jupyter Notebooks

  • Write Python programs using variables, data types, operators, conditionals, and loops

  • Design modular code using functions and modules

  • Use basic scientific computing practices (validation, tolerances, stopping criteria)

  • Solve mathematics-oriented programming exercises and document results in notebooks

  • Save and load results using simple file handling techniques