The Specialized Masters (SM) in Big Data at GEM/Ensimag, the Grenoble Institute of Engineering and Management's Grande Ecole for Computer Science and Applied Mathematics, provides you with the skills needed for data science and artificial intelligence. In addition to this, Agile Management, Law, Ethics, and Governance are all essential aspects of the program. A quick look at the experiences of two experts who are coming to the end of their training.eriences of two experts who are coming to the end of their training.
Anne Desbrières is a IT Engineer who graduated from the National Institute of Applied Sciences (INSA) of Lyon in 1990. She started out as a developer at Atos and then joined the R&D department at Hewlett Packard. "In 2008, I joined HP's Consulting Department as a Project Manager for telecom operators in the EMEA region (Europe, Middle East and Africa). I did project management for several years, managing international teams working on implementing 5G for "early adopters". Over the course of these experiences, I inevitably began to think about the content, value, and meaning of data in software solutions," she says.
Guillaume Chouteau, 44, is an Industrial Engineer and graduate of the Grenoble Institute of Engineering and Management. He has held various supply-chain-related positions at Becton & Dickinson, Caterpillar and Schneider Electric, and has worked on: production planning, supply team management, ERP development projects, and product launches. "By its very nature, the supply chain consumes and generates data through the use of integrated management software packages. And, in fact, global companies have a high level of organizational complexity. The handling of data value at these companies is complex and it is not done particularly well", he said.
"Too much "feeling" and not enough data aggregation"
Their respective experiences with data in the industrial and service sectors, and in particular with using data alongside artificial intelligence encouraged them both to embark on the GEM/Ensimag SM in Big Data in September 2020. Looking back over the past year, Guillaume Chouteau thinks about his experience: "The SM in Big Data provides individuals with the skills needed to extract, process, and analyze information, in order to generate added value for companies on a daily basis. This is needed because of the weaknesses within a company, which are far too often caused by large and intelligent data processing which integrates strategic approaches at a managerial level."
Technical requirements and developing strategic planning
The SM in Big Data is therefore generally aimed at people with technical expertise and a background in engineering. "The classes provide us with the fundamentals of the Big Data and AI professions through the study of databases and the use of data (data science and machine learning). What GEM offers us is an overview of data management and the knowledge of how to use data to generate added value. The professional training explores the legal aspects of protecting sensitive data, as well as the ethics surrounding data," explains Guillaume Chouteau. We examine things in depth and, in particular, we get perspective on the process."
This open-mindedness and perspective is essential to a critical and constructive approach to data. "When it comes to extracting value from data and structuring it so that it can be used, companies are currently in a maturity stage. The objective of the SM in Big Data is to be able to govern data and to extract value from it in order to make strong strategic planning possible."
Addressing data from a technical, managerial, ethical, and legal perspective
Anne Desbrières reflects on her own experience: "The course provided me with the academic resources to understand new technologies not only from a technical perspective, but also from a managerial, ethical, and legal perspective. I'm also developing an agile mindset - which is a bonus!" Indeed, through its case-study centered approach, the SM in Big Data program focuses in particular on Agile Management which is an essential part of data science. It teaches you how to understand client's needs, fulfil them, and how to improve the way in which you implement a project by using a Continuous Improvement Process. "On a technical level, going back to coding again was fun because I hadn't done it in over 15 years. The six-month internship in industry allowed me to develop my knowledge of neural networks. "
A new career path in data science
At 56 years old, Anne Desbrières plans to go into consulting, as a Data Scientist, Data Analyst, or Data Project Manager in the "Tech for good" sector. She is currently completing her end-of-study internship with eLichens, a start-up supported by its incubator CEA Leti, which specializes in air quality analysis. Anne is developing models for the company which predict pollen concentrations in the air. "Thanks to the valuable skills it promotes, this Master's program has allowed me to give myself some professional freedom", she emphasizes.
With 18 years of professional experience under his belt, and soon to be awarded the SM Double Degree in Big Data from GEM/Ensimag, Guillaume Chouteau is also envisaging the "Tech for good" sector (health, education, energy management, etc.). "I'm planning to write my professional Master's thesis on AI in healthcare; my internship is on renewable energies, and my Master's case study was related to education." He is also thinking about joining a start-up, "where AI is now an essential requirement for business models." He is nearing the end of a six-month operational internship at Probayses, in the Grenoble region, which is a research company (based at Inria Grenoble) specializing in AI for French and international industries.