ECO-4206 : Mathematics 2

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ECO-4206 : Mathematics 2

Responsable(s) :

Eric Thierry

Niveau

M1+M2

Discipline

Economie

ECTS

3.00

Période

2e semestre

Département

Département d'Économie

Localisation

Site Descartes

Année

2024

Public externe (ouverts aux auditeurs de cours)

Informations générales sur le cours : ECO-4206

Content objectif

ECO-4206 : Mathematics 2

This computer science course is intended for students wishing to learn or improve their programming skills. The programming language chosen will be Python, a language widely used both in teaching for its ease of access and in the professional world for its wide range of applications. In addition to learning Python syntax and creating small programs, this course will be an opportunity to discuss good programming practices, to try out algorithm design and analysis, and to learn how to use classic libraries of programs such as Matplotlib for data visualization, Pandas for data manipulation, or Scipy for scientific computation (related to the content of mathematics teaching).

Content prerequis

No programming prerequisite. Some exercises may refer to mathematical notions studied in previous courses, like linear algebra or differential calculus.

Each lecture will include a practical coding session. Therefore students will be asked to bring or share some device, like a laptop, where they can code in Python.

We strongly suggest to install the Ananconda distribution, which includes Python 3 and its main libraries, as well as tools like the Spyder Development Environment or the Jupyter Notebook (download the Individual Edition at : https://www.anaconda.com/products/individual).

Content modalites

This is an 8-week course with one 3 hours lecture, including practice session with computers, each week. Students will be evaluated on the basis of weekly homeworks (50%) and a final written exam (50%).

Content renseignements

The course is taught in English.

Content bibliographie

All the necessary educational material will be provided. The course will not require a particular textbook. But of course you can find many textbooks and online tutorials or apps teaching Python. Here are a few examples.

Textbooks:

"Python for kids" by Jason R. Briggs ("Python pour les kids" en version française), for an easy introduction to Python if you are completely new to programming.
"Think Python. How to think like a computer scientist" by Allen B. Downey, for a progressive introduction to Python (only core Python, it does not introduce the classical additional libraries). Free download on https://greenteapress.com/wp/think-python-2e/
"Python for Data Analysis" by Wes McKinney, for an introduction to data science with Python including the use of classical libraries like numpy, matplotlib, pandas (requires basic knowledge of Python).
"Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow" by Aurélien Géron, for a huge reference on Machine Learning with Python (requires basic knowledge of Python).

Online references:

Openclassrooms: https://openclassrooms.com/ (search for "Python" to get a list of courses ranging from beginner to expert)
SoloLearn: https://www.sololearn.com/ (free app for beginners)
Python Reference Site: https://www.python.org/ (with the latest documentation)

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Outils

ECO-4206 : Mathematics 2

Informations générales sur le cours : ECO-4206

Textbooks:

Online references: