Data Science & AI study track

Objectives

The Data Science track covers all aspects related to the exploitation, management and analysis of structured and unstructured data.

In practice

The course combines theoretical and practical components, ensuring a good balance of math seminars and practical work in the computer room. You will increase your knowledge of databases, web development, statistics and statistical learning.

Language of instruction: English

After the track

3rd year technological innovation at Télécom Paris

• Data Science
• Articial Intelligence

Master’s-Engineering Dual Degree

• Learning option:
  – Mathématiques, Vision, Learning (IP Paris/Univ. Paris-Saclay)
  – Data Science (IP Paris)
  – Data and Artificial Intelligence (IP Paris)
• Data Management option:
  – Data and Artificial Intelligence (IP Paris)
  – DataScale: Data management in a digital world (Univ. Paris-Saclay)

Professions

Career opportunities include data scientist or analyst, statistical engineer, database administrator, or careers in research and R&D in statistical learning, data management, data extraction, data mining, and learning mathematics.

Testimonial

The Data Science & Artificial Intelligence study tracke offers a particularly comprehensive course of study designed to provide an understanding of the fundamentals of modern artificial intelligence. It combines rigorous theoretical teaching in mathematics with a strong practical focus through numerous tutorials, practical sessions and group projects.

Throughout the year, the courses cover a variety of areas such as databases, machine learning, deep learning, text mining and graph mining. The aim is to gain an in-depth understanding of the mathematical and algorithmic mechanisms involved in designing these models, whilst developing the technical skills required to implement them. It is particularly rewarding to finally be able to understand, at least in part, how the technologies and tools that are playing an increasingly important role in our daily lives actually work.

— Tanguy Kolly, class of 2027