Short Track
Intake: September
Master of Science (MSc)
The MSc programme in Data Analytics for Business is a five-year programme that trains future managers specialising in the management and deployment of data projects and the digital transformation of companies. This specialised programme offers a comprehensive vision of the new disciplines linked to data and artificial intelligence as business accelerators.
SEMESTER 1
BOOTCAMP CODE
- Algorithmic
- Python
DIGITALISATION OF COMPANIES
- Digital strategies
- Digitalisation of business processes
- Management styles
- Inbound marketing
- Digital marketing
DATA ORGANISATION
- Data formats
- Data modelling
- Queries
- NoSQL/Hadoop/MapReduce
IMPACTS OF ARTIFICIAL INTELLIGENCE
- Ethics and artificial intelligence
- Legal dimensions of artificial intelligence
- Social impacts
- Economy of artificial intelligence
DATA VISUALISATION
- Descriptive statistics
- Multivariate analysis
- Dashboards
- Time series analysis
MACHINE LEARNING I (FUNDAMENTALS)
- Supervised learning (categorization and regression trees)
- Unsupervised learning (clustering)
- Reinforcement learning (Q-learning)
- Model validation
- Over- and under-fitting
- Cross validation
CONFERENCES, SEMINARS, SOFT SKILLS
SEMESTER 2
AGILE PROJECT MANAGEMENT
- Agile methods
- Management of project teams
- Specific methods and tools
- Customer relations
MACHINE LEARNING II (ADVANCED TECHNIQUES)
- Neural network
- Deep learning
- Random forest and xg boost
- Natural language processing
BUSINESS ANALYTICS
- Linear programming
- Non-linear programming
STOCHASTIC PROCESSES
- Time series and forecasting
- Simulation
BUSINESS AND AI
- AI and new business models
- Starting a new AI business
- Marketing of AI
IMPLEMENTING MACHINE LEARNING IN COMPANIES
- The different types of actors involved
- Information systems aspects
- Setting up a pipeline
- Maintenance and updates of models
CONFERENCES, SEMINARS, SOFT SKILLS
SUPPLEMENTARY PROJECTS
INTERNATIONAL INTERNSHIP
This internship allows students to convert their knowledge in data analytics during a 6-month internship in a multinational company.
FINAL DISSERTATION
Students select a relevant research question and write an academic assignment. They work closely with an academic supervisor who guides them through the various steps of their research.
Long Track
Intake: September
Regular Pathway
SEMESTER 1
Manager Skills
- Introduction to business management (Fast Track for Non-Managers)
- Strategic management
- Financial performance management
- Business & Sustainability
- Public speaking
- Visual communication & Design
- Data management
- Hard skills
- TOSA Excel
- TOEIC
- Orthodidacte
- French/English as a second language
Expertise skills
- Marketing studies
- Data visualisation
- Digital experience
SEMESTER 2
INNOVATIVE & ENTREPRENEURIAL SKILLS
-Innovation management and entrepreneurship
-Complexity Management
-Coding skills
-Corporate project
CORPORATE PROJECT
A consultancy mission on a real and current issue of a company. Corporate projects enable participants to gain valuable hands-on experience of business conduct and strategy and deal with the practical complexities. Students are guided by their KEDGE tutor
throughout the project. The assignment is done in groups of 4 to 5 students. A combination of collective and individual work. Final presentation in front of the corporate and KEDGE tutors.
POSSIBILITY TO COMPLETE ONE SEMESTER ABROAD AT A PARTNER UNIVERSITY
Your choice of experience
- INTERNSHIP in France or abroad
- PROJECT: Associative, entrepreneurship...
- LEARNING TRIP ABROAD: You can find a job or take some language courses
- OTHER CORPORATE PROJECT
Master of Science (MSc)
Semester 1
BOOTCAMP CODE
- Algorithmic
- Python
DIGITALISATION OF COMPANIES
- Digital strategies
- Digitalisation of business processes
- Management styles
- Inbound marketing
- Digital marketing
MANAGEMENT STYLES
- Inbound marketing
- Digital marketing
DATA ORGANISATION
- Data formats
- Data modelling
- Queries
- NoSQL/Hadoop/MapReduce
IMPACTS OF ARTIFICIAL INTELLIGENCE
- Ethics and artificial intelligence
- Legal dimensions of artificial intelligence
- Social impacts
- Economy of artificial intelligence
DATA VISUALISATION
- Descriptive statistics
- Multivariate analysis
- Dashboards
- Time series analysis
MACHINE LEARNING I (FUNDAMENTALS)
- Supervised learning (categorization and regression trees)
- Unsupervised learning (clustering)
- Reinforcement learning (Q-learning)
- Model validation
- Over- and under-fitting
- Cross validation
CONFERENCES, SEMINARS, SOFT SKILLS
Semester 2
AGILE PROJECT MANAGEMENT
- Agile methods
- Management of project teams
- Specific methods and tools
- Customer relations
MACHINE LEARNING II (ADVANCED TECHNIQUES)
- Neural network
- Deep learning
- Random forest and xg boost
- Natural language processing
BUSINESS ANALYTICS
- Linear programming
- Non-linear programming
STOCHASTIC PROCESSES
- Time series and forecasting
- Simulation
BUSINESS AND AI
- AI and new business models
- Starting a new AI business
- Marketing of AI
IMPLEMENTING MACHINE LEARNING IN COMPANIES
- The different types of actors involved
- Information systems aspects
- Setting up a pipeline
- Maintenance and updates of models
CONFERENCES, SEMINARS, SOFT SKILLS
Supplementary contents
INTERNATIONAL INTERNSHIP
Enables students to apply data analytics that they have learnt during a six month assignment within a multinational company.
FINAL DISSERTATION
Students select a relevant research question and write an academic assignment. They work closely with an academic supervisor who guides them through the various steps of their research.
CONDENSED TRACK
Fast Pathway
Enter the specialisation year in just a few months by choosing the condensed track that provides the prerequisites in just 4 months.
Bordeaux campus
SUMMER SCHOOL PROGRAMME
Includes business and cultural visits at no additional cost.
5 or 6 courses of your choice among the following list
Supply Chain
- Design of the Supply Chain
- Management of the Supply Chain
Value creation & digital marketing
- Value creation & brand management
- Digital Marketing for Entrepreneur
- Entrepreneurship
Wine tourism
- French wine industry
- Oenotourism
FUNDAMENTALS & SOFT SKILLS PROGRAMME
3 courses of your choice among the following list
- Data Management
- Team Management
- Video Communication & Design
- Public Speaking & leadership
- International Management
CORPORATE PROJECT
The mission is carried out in groups of 4 to 5 students and combines collective and individual work. The final project is presented to the company and the KEDGE tutor
French as Foreign Language
Marseille campus
SUMMER SCHOOL PROGRAMME
Includes business and cultural visits at no additional cost.
5 or 6 courses of your choice among the following list
Sports management & marketing
- Strategic management & advanced marketing for sport organizations
- Sport marketing & communication
Design thinking
- Managing the creative process
- Design thinking
Social business
- Social business, territories & innovations
- Sustainable entrepreneurship
Global Finance & International Business
- Global Finance Regulations or Managerial Cost Accounting
- International Business : A Mediterranean Perspective
Ethics in business and society
- Ethics in business & society
- Towards sustainability
FUNDAMENTALS & SOFT SKILLS PROGRAMME
3 courses of your choice among the following list
- Data Management
- Team Management
- Video Communication & Design
- Public Speaking & leadership
- International Management
CORPORATE PROJECT
- The mission is carried out in groups of 4 to 5 students and combines collective and individual work. The final project is presented to the company and the KEDGE tutor.
French as Foreign Language
Master of Science (MSc)
CURRICULUM
SEMESTER 1
BOOTCAMP CODE
- Algorithmic
- Python
DIGITALISATION OF COMPANIES
- Digital strategies
- Digitalisation of business processes
- Management styles
- Inbound marketing
- Digital marketing
MANAGEMENT STYLES
- Inbound marketing
- Digital marketing
DATA ORGANISATION
- Data formats
- Data modelling
- Queries
- NoSQL/Hadoop/MapReduce
IMPACTS OF ARTIFICIAL INTELLIGENCE
- Ethics and artificial intelligence
- Legal dimensions of artificial intelligence
- Social impacts
- Economy of artificial intelligence
DATA VISUALISATION
- Descriptive statistics
- Multivariate analysis
- Dashboards
- Time series analysis
MACHINE LEARNING I (FUNDAMENTALS)
- Supervised learning (categorization and regression trees)
- Unsupervised learning (clustering)
- Reinforcement learning (Q-learning)
- Model validation
- Over- and under-fitting
- Cross validation
CONFERENCES, SEMINARS, SOFT SKILLS
SEMESTER 2
AGILE PROJECT MANAGEMENT
- Agile methods
- Management of project teams
- Specific methods and tools
- Customer relations
MACHINE LEARNING II (ADVANCED TECHNIQUES)
- Neural network
- Deep learning
- Random forest and xg boost
- Natural language processing
BUSINESS ANALYTICS
- Linear programming
- Non-linear programming
STOCHASTIC PROCESSES
- Time series and forecasting
- Simulation
BUSINESS AND AI
- AI and new business models
- Starting a new AI business
- Marketing of AI
IMPLEMENTING MACHINE LEARNING IN COMPANIES
- The different types of actors involved
- Information systems aspects
- Setting up a pipeline
- Maintenance and updates of models
CONFERENCES, SEMINARS, SOFT SKILLS
SUPPLEMENTARY CONTENTS
INTERNATIONAL INTERNSHIP
Enables students to apply data analytics that they have learnt during a six month assignment within a multinational company.
FINAL DISSERTATION
Students select a relevant research question and write an academic assignment. They work closely with an academic supervisor who guides them through the various steps of their research.
