IIn this tutorial, you will learn the fundamentals of Python programming and how to use it for data analysis and visualisation. We will start with an introduction to Python and cover topics such as data types, control flow, functions, and libraries.
Next, we will dive into data science and explore topics such as data cleaning, manipulation, and visualisation. You will learn how to work with data using popular Python libraries such as NumPy, Pandas, and Matplotlib.
Silvia TULLI
Atelier
English
Students are required to complete a Python exercise on a weekly basis and an assignment every two weeks
This tutorial is designed for the students of the Digital and Public Policy stream who want to enhance their skills in programming, data analysis and data visualisation after the bootcamp.
Please note that this tutorial is independent from the elective course “Data science for public policy”.
.
Autumn 2024-2025
The evaluation modality for this Python Tutorial consists of 3 graded assignments that will be used to determine the final grade (fail/pass). The assignments will be graded based on their accuracy, completeness, and adherence to best practices in Python and data science.
As part of the continuous assessment, students' participation will be graded, but it will not represent more than 10% of the final grade..
To validate the course, students must achieve a pass grade. This grade will be determined based on the overall performance in the graded assignments, including the participation grade.
This is a 12 hour workshop (2h each two weeks).
Think Python (2nd Edition), by Allen B. Downey, is a substantially revised version of How to Think Like a Computer Scientist Learning with Python. It is available for free in various formats; printed copies can be purchased as well: https://greenteapress