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BBA-Data Sciences

BACHELOR'S IN BUSINESS ADMINISTRATION - INTERNATIONAL
DATA SCIENCES - LEVEL 6 EQF 

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Specialization

Data Sciences


Location

Lyon, France | Remote | Hybride

Language

English or French 

Pedagogical methods

Theoretical courses, tutorials and practical work Case studies and professional scenarios Individual and group projects  

Target group

Students - people seeking employment - employees and professionals in the sector

Level

6 EQF (European Qualifications Framework)


Credits

180 ECTS 

Sessions

 Spring (March), Summer (July),  Fall (October)

Admission requirements

  • High School Diploma or equivalent (start in 1st year)
  • Level 5 EQF qualification or a qualification equivalent to the attainment of 120 ECTS (start in 3rd year)

Course Structure

Full-time or work-study

multicolored codes

Overview

The Bachelor in Data Science is a 3-year program that equips students with the technical, analytical, and strategic skills to transform data into valuable insights. This interdisciplinary degree blends computer science, mathematics, and business knowledge to prepare students for high-impact roles in the data-driven economy.

Students learn to collect, clean, analyze, and visualize data using modern tools and programming languages. The program emphasizes hands-on projects, ethical data usage, and real-world problem solving. Whether aiming to work in tech, finance, healthcare, marketing, or research, this bachelor provides a solid foundation for success in a wide range of industries.

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Career Opportunities

Graduates of the Bachelor in Data Science can pursue roles such as:

  • Data Analyst
  • Data Scientist
  • Machine Learning Engineer
  • Business Intelligence Analyst
  • AI Developer
  • Data Engineer
  • Quantitative Analyst
  • Operations Analyst
  • Research Scientist
  • Continued studies in Master’s programs (AI, Data Science, Statistics, etc.)

Program Learning Outcomes

By the end of the program, students will be able to:

  • Master core programming languages such as Python, R, and SQL
  • Apply mathematical and statistical techniques to analyze large datasets
  • Develop and evaluate machine learning models
  • Visualize data effectively to support decision-making
  • Understand data ethics, privacy, and legal regulations
  • Communicate technical results clearly to non-technical audiences
  • Work in interdisciplinary teams on real-world data projects
  • Deploy data pipelines and predictive models using industry tools

Programs :

Year 1: Foundations

  • Introduction to Programming (Python)
  • Linear Algebra & Calculus for Data Science
  • Statistics & Probability
  • Data Visualization Basics
  • Introduction to Databases (SQL)
  • Digital Ethics & Data Privacy
  • Communication & Scientific Writing

Year 2: Core Competencies

  • Machine Learning Fundamentals
  • Advanced Data Analysis with R
  • Data Engineering & Cloud Tools
  • Algorithms & Data Structures
  • Data Storytelling & Dashboard Design
  • Applied Project I: Analytics for Business
  • Internship (8–12 weeks)

Year 3: Specialization & Application

  • Deep Learning & AI Applications
  • Natural Language Processing (NLP)
  • Big Data Technologies (Spark, Hadoop)
  • Predictive Modeling & Deployment (MLOps)
  • Capstone Project: Full Data Pipeline
  • Optional Special Topics (Health Data, Fintech, etc.)
  • Internship or Research Project (12–16 weeks)