ESIEA Graduate School of Engineering in partnership with SKEMA Business School offers you a new program in Artificial Intelligence. This unique program brings together the expertise of a major Engineering school and a leading Global Business school

 

Program Overview

 

This English-taught program begins in September 2019 on the Paris campus.

Skema Business School is a major international Business school in Paris, Lille and Sophia- Antipolis. It is a member of the Conférence des Grandes Ecoles and accredited EQUIS; it issues a Grande École degree (Master Bac+5) approved by the Ministry of Higher Education and Research

Coming from two different worlds, ESIEA and SKEMA share a common pedagogy and values such as a high-level modular educational program, active pedagogy, project development, personal development and research and development.

 

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Program Content

 

From information systems to logistics, customer data and human resources, data is everywhere and awaits only one thing: to be processed and used intelligently to drive projects and inform decisions.

To do this, managers must adopt an analytical and scientific approach. They must be able to understand the data, make it “speak” using algorithms and return their analyses to a non-expert audience.

The objective of this program is to train future managers so that they are able to understand, use and even develop artificial intelligence and data visualization algorithms in order to offer innovative technical solutions to companies’ business problems.

Our hybrid program will allow engineering, business and other students to pursue international training, to become multidisciplinary team players, to acquire excellent interpersonal skills, to show openness and curiosity, to have the ability to solve technical problems and to understand and develop projects with a strong artificial intelligence component.

Who can apply ?

 

  • MSc in 1 year: holders of a Bac+4 (4-year Bachelor’s or 1-year Master’s degree)
  • MSc in 2 years: holders of a Bac+3 (3-year Bachelor’s)

 

Autumn semester, 30 credits

  • Artificial Intelligence, Challenges and Tools, Introduction to Data Science

Become aware of the economic impact of digital disruption. Understand opportunities and connections in the data processing chain for value creation.

2 credits, taught by ESIEA
  • Overview of the Existing System

Learn analysis and visualisation solutions and techniques. Get to know the main algorithms and structures, neural networks, machine learning, deep learning. Keep up to date with the latest technological developments.

4 credits, taught by ESIEA /SKEMA
  • Business Solutions Management

Mastering the ecosystems and tools, project management, legal aspects (RGPD)

2 credits, taught by ESIEA
  • Cloud Computing

Understand the concept of virtualisation. Know the different architectures: public, private, hybrid cloud. Be aware of the issues of confidentiality, sovereignty and costs.

1 credit, taught by ESIEA
  • Big Data Architectures

Learn Spark, Hadoop, MapReduce

2 credits, taught by ESIEA
  • Advanced Management and Implementation of Solutions

Understand the techniques of real-time data analysis (log processing). Know blockchain. Ensure data quality and governance.

2 credits, taught by ESIEA /SKEMA
  • Smart Home 
2 credits, taught by ESIEA

 

  • Cyber Security 
2 credits, taught by ESIEA

 

  • Preparation for writing the thesis + identification, qualification, analysis of information and developments in AI 

(group project with feedback throughout the two semesters)

2 credits, taught by SKEMA

 

Spring semester, 30 credits

 

  • Corporate Strategy, Law and Ethics 
5 credits, taught by SKEMA
  • Change Management
2 credits, taught by ESIEA /SKEMA

 

  • Digital Consulting / Consulting Methods
2 credits, taught by ESIEA /SKEMA

 

  • Start-up / Creativity / Entrepreneurship 
2 credits, taught by SKEMA

 

  • Project in groups over the year, provided by companies, mentoring + 
5 credits, taught by various companies

 

  • In-company modules (2 credits each, taught by various companies)

– Microsoft

– Acticall / AI client experience

– IBM / Watson Application

– Accenture

– Devoteam

– Facebook

 

Professional thesis : 30 credits

TOTAL  CREDITS : 90

 

Programme goals

The Learning objectives of the program are to develop the following:

 

1- AI skills

  • Understand the basics and functioning of AI and its challenges
  • Learn about the different tools/platforms/algorithms
  • Choose the right tools/platforms/algorithms for given problems and how to deal with them
  • Keep abreast of the latest developments in AI

2- Change management and Project management skills

3- Cybersecurity skills

Understand the risks and impacts on companies, in coordination with cybersecurity specialists; ability to manage cybersecurity aspects and confidential information.

4- General skills

Develop interrelational skills, multidisciplinary team management and communication skills, creativity, and find innovative solutions

5- Ability to analyze Ethical implications

6- Awareness of regulatory and legal issues at an international level.

 

Admission Schedule

Due to the limited number of places available, we encourage candidates to apply as soon as possible.

 

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