Parcours de formation "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)

Conditions d'obtention du diplôme : La validation de l’ensemble des requis diplômants est obligatoire. La confirmation de la diplomation sera effectuée par le jury de diplôme.

Modalités d'évaluation :

Les méthodes d’évaluation peuvent inclure une variété d'approches telles que des études de cas, des présentations, des exercices pratiques, des tests écrits, des projets de groupe, et des évaluations orales. Ces différentes méthodes permettent de mesurer les compétences et les connaissances acquises de manière approfondie et diversifiée.