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Automation, robotics, sensors - 2020 New

Artificial intelligence & data science : business applications and implementation strategy


The objective of this training is to raise awareness and understanding of the issues, key concepts and business applications of Data Science (the field of Artificial Intelligence).

This course is for those wishing to:

  • Understand the basic principles of Data Science
  • Understand business applications so that they can be broken down into their organization/business areas
  • Implement a Data Science approach and to experiment through a Data Lab
  • Know how to measure the impact, value and constraints of Data Science
  • Be familiar with GDPR and the constraints around the management and security of data


The course lasts 1 days (8 hours).


In addition to theoretical and methodological input, the following teaching techniques will be implemented:

  • Examples of specific cases (approaches and
    routine cases): at least 25%
  • Discussions and idea workshops: at least 25%


Course level : Basic
No specific knowledge on Data Science or Artificial Intelligence required.

Target audience:

Managers and industry/support roles using data to make decisions and create value for the company's products/processes/services:

  • Managers (directors, organization heads)
  • Industry team leaders (all roles)
  • Innovation managers
  • R&T managers
  • IT managers
  • Chief data officers


Sébastien COPPOLA :

Engineer at l’ISAE-SUPAERO*, Data Science Project Manager at Aqsone, 11 years of experience in Digital Transformation *Institut Supérieur de l’Aéronautique et de l’Espace or National Higher French Institute of Aeronautics and Space

Olivier REBERGA :

PhD in Fluid Mechanics at SUPAERO, Data Science Project Manager at Aqsone, 18 years of experience in IT.


  • Key principles and definitions
    • Artificial Intelligence
    • Big Data
    • Data Science
    • Analytics
  • Industrial application in the various fields
    • Design
    • Manufacturing
    • Client Support & Services
    • Transverse functions: Supply Chain, Purchasing.
      Quality, HR, Finance, etc.
    • Information Systems
  • Illustrations through approaches and routine cases used by the facilitator
  • Feedback of experience and discussions among participants
  • State of the Industry: examples from different industries, Data Science maturity grid
  • Interactive session (workshop) to identify routine cases with on course participants
  • Strategy and process to implement a Data Science approach
    • Prerequisites (human, technical and data)
    • Key stages
    • Impacts on organization, skills,
      information systems
  • Overview of an end-to-end Data Science process
    • Identification of a sector-specific problem
      or an innovation
    • Acquisition of the data
    • Analysis, development of algorithms
      and predictive models
    • Visualization and UX/UI
  • Introduction to Data Lab mode to quickly experiment in Agile mode before deploying an industrial Data Analytics platform
  • Value and Benefits of Data Science: How to measure impact (value versus effort and risk)
  • Introduction to GDPR constraints and Security
  • Concepts of Architecture and Data Governance
    • Data Platform
    • Data Hub
    • Data Lake


Scheduled in French:

TOULOUSE : June 8, 2020

(Initially schedulded March 9, 2020)


For the English realization, please, consult us.


€590 excluding tax (20% VAT)

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