Data Analytics for Business

Build bridges between Data Science and Business

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Admission level

From Bachelor's degree - 3 years to Bachelor's degree - 4 years, Validation of Personal and Professional Experience (VAPP)

Campus

Bordeaux

Degree

MSc, Master of Science

Format

Full Time

Intake

September 2023

Language

English

Overview of the Master of Science (MSc) in Data Analytics for Business

This Master of Science programme 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.

 

  • MSc Data Analytics for Business
KEDGE Master of Science Data Analytics for Business

Discover KEDGE Master of Science in Data Analytics for Business

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 Master of Science (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 PROGRAMME IN DATA ANALYTICS FOR BUSINESS

  • 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

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

  • Microsoft
  • Digital Aquitaine
  • Trustworthy AI Chair

Skills developed during the MSc programme in Data Analytics for Business

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.

  • 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 Master of Science (MSc) in Data Analytics for Business is taught on the Bordeaux campus.

campusbordeauxmin

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 Data Analytics for Business programme

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

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