Présentation TAF Data Science

Data science relies on the synergy between business expertise, mathematics, and computer science to extract value from data.

What you will learn How to create value from data while integrating economic and societal dimensions? How to design, evaluate, and deploy Machine Learning solutions? How to manage and analyze massive data using Big Data technologies?

 

A Distinctive Approach

Our ambition is to enable IMT Atlantique engineers to leverage the data resources they will encounter. Through interaction with decision-makers, they will learn to formulate value-creation challenges, identify key data, manage it, implement processing and analysis systems, and produce summaries aligned with business strategy.

This specialization stands out through its comprehensive approach: business expertise, mathematics, and computer science, while incorporating economic, legal, and social aspects.

Developed Skills

With this specialization, we offer 3 career paths: Data Science & Machine Learning (focusing on algorithms and modeling), Data Engineering & Architecture (focusing on infrastructure), and Data & Analytics (focusing on decision support).

The skills acquired in our Core courses revolve around four fundamental areas:

• Applied Statistics: mastery of mathematical foundations for data analysis and machine learning
• Machine Learning: understanding and implementation of essential learning algorithms and advanced AI techniques
• Computer Science for Data Science: mastery of data science tools and development environments
• Data Society: understanding of economic, legal, and ethical implications of data

 

Three major career families

These fundamental skills are enhanced by specific expertise aligned with three major career families:

Data Science & Machine Learning

• Design and implementation of complex predictive models
• Optimization and industrialization of AI solutions
• Validation and deployment of models in production

 

Data & Analytics

• Exploratory analysis and advanced data visualization
• Construction of decision-making dashboards
• Supporting decision-makers in data exploitation

 

Data Engineering & Architecture

• Design of distributed architectures for massive data processing
• Implementation of robust and scalable data pipelines
• Management of data quality and security

 

The pathways we offer provide a progression of courses linked to one or more of these career families.

Practical implementation

The program emphasizes a hands-on approach where students apply their knowledge to real cases. They develop concrete expertise in data management and analysis while mastering the necessary IT tools. This practical experience spans various business domains, allowing students to understand the specificities of each sector.

Admission

Admission to the Specialization

The Data Science specialization is open to both 2nd and 3rd year students. It also welcomes international students, some of whom follow our Master of Science IT - Data Science program.

The selection criteria are as follows:

• Have balanced results (not having neglected any discipline) with particular attention to computer science, mathematics, and social sciences
• Show motivation: a coherent professional project, business experience, and personal achievements (git repositories) in the field are differentiating elements to highlight

Please note: Due to high demand, only students who requested the Data Science specialization as their first choice are considered.

If you are in your first year, it is advisable to apply for the specialization in your second year to help us manage enrollment flows.

Admission to Pathways

The prerequisites for different pathways are indicated in the pathway descriptions on the dedicated page.

For eligible students, those who have completed the Core Teaching Units (ABCD) of the specialization (current or previous year) remain priority candidates.