• Votre sélection est vide.

    Enregistrez les diplômes, parcours ou enseignements de votre choix.

Applied Data Science in Finance (Python)

  • Niveau d'étude

    BAC +5

  • ECTS

    3 crédits

  • Composante

    Ecole d'économie de la Sorbonne (EES)

  • Volume horaire


  • Période de l'année



Summary: Through three applications, the course will provide an introduction to Data Science in Finance. Each project (6 hours) will be divided into three sessions:

  1. A presentation of the problematic and a discussion about the tools and the methodology that could be used by students.
  2. A session during which students work in groups on the project and ask questions (debugging).
  3. A presentation of the project to the class by the students.

- The first project will consist of creating a WebApp, using Microsoft Azure, Python and MongoDB, to gather and display financial data on a website.

- The second project will consist of extracting data from the Wall Street Journal website before implementing natural language processing to automatically convert textual content into quantitative indicators.

- The third project will consist of creating a real-time trading strategy by analysing the content published on Twitter about listed companies.

The language used for the course is Python.

Professor: Thomas Renault (Assistant Professor of Economics - University Paris 1 Panthéon-Sorbonne)

Student assessment: Project (submission + presentation)

Lire plus


  1. (6 hours) Project #1: Building a Financial WebApp
  2. (6 hours) Project #2: Web scrapping and Natural Language Processing 
  3. (6 hours) Project #3: Implementing a trading strategy based on Twitter data
Lire plus