Curriculum "Data Analytics for Business"

Semester 1 

• Strategic thinking
• Financial performance 
• Data management
• Excel certification (TOSA)
• Business & ecological transition
• Business & social change
• Ecological challenge & organisational management
• Public speaking
• Visual communication & sustainable impakt

Semester 2 

• Team management
• Business & sustainability
• ChatGPT leadership lab 
• Coding skills 
• Open Innovation Challenge (applied corporate project)

Pre-specialisation courses

• Marketing reconsidered
• Qualitative & quantitative research
• Procurement (Paris)
• Digital analytics (Python) (Bordeaux)

Additional content

• 4- month internship (in France or abroad) or academic partnership

BOOTCAMP CODE

• Algorithmic
• Python

DIGITALISATION OF COMPANIES

• Digital strategies
• Digitalisation of business processes
• Management styles
• Inbound marketing
• Digital marketing

MANAGEMENT STYLES

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

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

• International internship
• Final dissertation
• Paris study trip
• Hackathon
• Certification Azure AI-900
• Certification PSM 1 (professional scrum master)

Degree requirements:

All degree requirements must be successfully completed. The awarding of the diploma will be confirmed by the examination board.

Assessment methods:

Evaluation methods may include a variety of approaches such as case studies, presentations, practical exercises, written tests, group projects, and oral assessments. These diverse methods allow for a comprehensive and in-depth evaluation of the skills and knowledge acquired.