Summer programme – AI Business

Final year Undergraduate or Master students
Languages : English

Earn a certificate in AI Business and take credit-awarding modules

Mission

Earn a certificate in AI Business and take credit-awarding modules

  • Develop competences from basics to advanced in Python application of the new business tools of data science.
  • Apply machine learning and deep learning to business data analysis.
  • Create business intelligence through application and visualization.
  • Learn from automated analysis of text and networks.
  • Develop AI business projects to showcase your skills to future employers.
  • Build a deeper understanding of complex environments and how to derive an advantage from them.

Four AI business courses compose the programme:

  • Data Science for Business
  • AI Business Intelligence
  • Business Textual Learning
  • Business Network intelligence

Admissions

Data Science for Business

Pre-requisites

  • Sucessful completion of at least two years of undergraduate level studies
  • Strong command of spoken and written English

AI Business Intelligence

Prerequisites

  • Successful completion of at least two years of undergraduate level studies.
  • Coding experience or attend the «Data Science for Business» class before
  • Strong command of spoken and written English

Business Textual Learning

Prerequisite

  • Successful completion of at least two years of undergraduate level studies.
  • Coding experience or attend the «Data Science for Business» class before
  • Strong command of spoken and written English

Business Network Intelligence

Prerequisites

  • Sucessful completion of at least two years of undergraduate level studies
  • Coding experience or attend the «Data Science for Business» class before
  • Strong command of spoken and written English

Programme

Four AI business courses compose the programme:

Data Science for Business


This module starts with the very basics of Python coding and works up modern advanced techniques such as machine learning and deep learning.
The field of data science for business is the context for the class, and so applied business examples are the focus. The module is very practical – you will follow the lessons using shared Python codebooks and implement the techniques along with the professor.

Topics covered

  • Learn Python from the very beginning
  • Master machine learning for business
  • Understand AI deep learning techniques
  • Apply learning to real business datasets

AI Business Intelligence


In business data science we take business data and create business intelligence. This module focuses on the creation and presentation of that business intelligence. You will work primarily on Tableau (for which a personal license will be provided to you), the leading intelligence generation and visualization platform in modern business.

Topics covered

  • Develop expert Tableau knowledge
  • Apply Python for data visualisation
  • Understand business intelligence needs
  • Generate automated BI reporting

Business Textual Learning


How to automate creating knowledge from written documents is still in its infancy. Largely people still manually read documents in order to extract intelligence from them. But data science, through its natural language processing field, offers fascinating new techniques to automate generating knowledge from text. This module brings you on a journey through the practical application of the most business relevant of the techniques in this area.

Topics covered

  • Extract knowledge from text
  • Apply natural language processing
  • Learn new science of topic modelling
  • Measure text sentiment and complexity

Business Network Intelligence


The best businesses make effective use of their networks – such as their workforce and their external connections including customers and social media networks. They might crowdsource intelligence, customers, and funding. In this module we show how new data science techniques allow the extraction of business intelligence from the firm’s diverse networks.

Topics covered

  • Understand connectivity of today’s society
  • Analyse social and business networks
  • Learn network visualization techniques
  • Apply big data techniques and analytics

Calendar

Registration deadline: February 14th 2022 for class 1 and class 2; April 1st for class 3 and class 4

Data Science for Business class 1 - VIRTUAL

March 21 – Class begins virtually with asynchronous work. Synchronous sessions held the weekend of March 26-27. Asynchronous work/projects to conclude April 1

AI Business Intelligence class 2 - VIRTUAL


April 4 – Class begins virtually with asynchronous work. Synchronous sessions held the weekend of April 9-10. Asynchronous work/projects to conclude April 15

Business Textual Learning class 3 - IN RENNES


May 17 – Class begins in person. Class days : May 17-20, May 23

Business Network Intelligence class 4 - IN RENNES


May 24 – Class 4 begins in person. Class days : May 24-25, 27-28 and 30

Fees

Fees 2022: between 900€ and 3000€ depending on the number of classes

Included in the programme:

  • 30 hours of classroom teaching per course
  • Teaching material

Assessment method: Assessment by means of a group project developed within the class, and daily assessment sheets

“So, are you convinced?”
Do you have any questions about whether you are eligible to apply? Contact your advisor
Laura Meunier