MSc Data Analytics for Business

Build bridges between Data Science and Business

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Admission level

From Bac +3 to Bac +5

Campus

Bordeaux

Degree

Master of Science

Format

Full time

Intake

September 2022

Language

English

Overview of the MSc in Data Analytics for Business

This Master of Science prepares students to become professionals with the ability to bridge the gap between data specialists and processing techniques and the various business lines. Ultimately, they will be experts in the field of data and the digital transformation of companies.

 

Olivier DUPOUET - KEDGE

campus of Bordeaux

Olivier DUPOUET

THE OBJECTIVES OF THIS TRAINING IN DATA ANALYTICS

Artificial intelligence (AI), machine learning and business analytics techniques are becoming increasingly important in companies, enabling them to invent and create new, value-generating businesses.

However, as these technical specialities develop, it appears that a crucial link is currently missing: professionals capable of bridging the gap between data specialists and other business areas.

The MSc in Data Analytics for Business is built on three pillars essential to the success of the digital transformation of companies:

    Modelling, based on machine learning and business analytics techniques, which enable companies to improve their operational excellence and develop new business models.
    Understanding information systems, which are the infrastructure for deploying models.
    Knowledge of the company's businesses and major functions, which initiate projects and ultimately use the applications.

Programme's Labels :

Bienvenue en France

HIGHLIGHTS OF THE MSc DATA ANALYTICS FOR BUSINESS

A COMPREHENSIVE MANAGEMENT APPROACH

  • Digital business strategy
  • Ethical considerations
  • Legal aspects
  • Soft skills
    • Public speaking & leadership
    • Team management
  • User eXperience, User Interface
  • Agile project management
  • Design thinking
  • Business models
  • Use cases in:
    • Finance
    • Marketing
    • Logistics

A GLOBAL APPROACH TO DATA

  • Programming language (Python, SQL)
  • Machine learning algorithms
  • Data mining
  • Data organisation and management
  • Data visualisation
  • Business intelligence
  • Business Analytics
  • Information systems management

EXPERIENTIAL LEARNING

  • Microsoft
  • Digital Aquitaine
  • Trustworthy AI Chair

Skills developed during the MSc in Data Analytics for Business

TECHNICAL KNOWLEDGE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

While not necessarily becoming experts in these fields, it is essential that graduates are able to understand the main principles and logic underlying the activities of data scientists:

  • Understanding what data is, what the main sources are and what forms it can take.
  • Mastery of the basic concepts around the most popular algorithms.
  • Understanding of what can be done with these tools.
  • Master the techniques for evaluating the quality of algorithms and identifying potential sources of problems.

MASTERING THE MANAGEMENT TECHNIQUES ASSOCIATED WITH THIS MEDIATION ROLE IN THE SPECIFIC CONTEXT OF ARTIFICIAL INTELLIGENCE

  • Learning the techniques of agile project management
  • Understanding of the strategic and organisational issues associated with the introduction of artificial intelligence tools into the company's processes.
  • Understanding of the ethical issues associated with the use of these techniques.

Bordeaux Campus

The MSc in Data Analytics for Business is taught on the Bordeaux campus.



Designed as a living space like the British universities, this 35,000 m2 campus combines work, sports and relaxation areas. Innovative facilities that are particularly well suited to the needs of the new generation of students.

Find out more about Bordeaux campus

Careers after the MSc in Data Analytics for Business

In management, team management or project management, the career opportunities offered by the data analytics for business training course on completion are numerous:

  • Project manager and project management assistance
  • Project manager and product owner
  • Consultant, AI development advisor
  • Manager of data scientists
  • Business engineer in the field of AI
  • Digital transformation

More about careers

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