Télécom ParisTech

Big Data at Telecom ParisTech - Data Scientist - Machine Learning

The dynamism of the Big Data courses at Télécom ParisTech is the result of strategic and unique multidisciplinary research in Europe. They are built around many subjects: financial mathematics, graph-mining and exploring social networks, ranking and collaborative filtering, attack detection, Internet advertising, and indexing/searching multi-media documents, but also examine the legal, economic, political, and philosophical aspects in relation to the use of personal data.

Big Data is one of Télécom ParisTech's six major defining strategies across its four departments. A key component of its international reputation, it is reflected in its three goals: education, research, and innovation.

The Grande École runs three Research and Teaching Chairs in Big Data and offers a comprehensive range of courses in formal and continuing professional education. It encourages innovation via its incubator, ParisTech Entrepreneurs. The subject involves 13 lecturer-researchers, 50 doctoral students, and about a hundred graduates per year.

Big Data brochure to share and download on Slideshare 

Big Data: a priority and national issue

Big Data is part of the national priorities set out by the French government with the Big Data Plan launched in 2013, which aims to make France the world reference in this field, particularly through the education of data scientists. At European level, Big Data was included in the roadmap of the Seventh Framework Programme, and nowadays is in the spotlight in the Horizon 2020 Programme.

Big Data: professions of the future

The Big Data Plan presented by the Government in June 2014 estimates that 10,000 direct jobs will be created by 2019 for a value creation of 2.8 billion euros. Depending on their experience, Big Data professionals are eligible for the positions of data analyst, data scientist, Big Data IT systems architect, Chief Data Officer (CDO), Data Protection Officer (DPO) or even data visualisation expert.

13 Professors & Associate Professors

50 PhD students

4 Departments – A comprehensive multidisciplinary coverage

Signal Processing

  • Machine Learning
  • Distributed Optimisation
  • Multimedia big data

Computer Science and Networks

  • Web Data Mining/Semantics
  • Parsimonious and distributed protection
  • Data distribution

Electronic Communication

  • Distributed storage
  • Distributed Optimisation

Social and Economic Sciences

  • Visualisation
  • Economics and business models
  • Personal Data Law
  • Big Data Public Policy
  • Big Data Sociology

Research chairs

Télécom ParisTech, in partnership with businesses and with the support of the Télécom Foundation, is involved in three chairs in its group, Institut Mines-Télécom, related to the field of Big Data.

Machine Learning for Big Data

Founded in 2013 and led by Prof. Stéphan Clémençon, the Chair conducts research at the interface of mathematics and computer science. Machine Learning aims to develop algorithms enabling machines to learn automatically from data, and thus improve their performance. There are four partner companies: Criteo, PSA Peugeot Citroën, Safran and BNP Paribas.
machinelearningforbigdata.telecom-paristech.fr

Big Data & Market Insights

This chair, which was founded in 2014 in partnership with the Télécom Management School, is led by Talel Abdessalem (Professor in the Computer Science and Networks Department) and brings together researchers specialised in the principles of big data management and mining, knowledge extraction from the web, and social network analysis. The Chair, founded with the support of the Télécom Foundation, is funded by Deloitte, Groupe BPCE, Groupe Rocher (formerly Groupe Yves Rocher) and Voyages-sncf.com.
bdmi.wp.mines-telecom.fr

Values and Policies of Personal Information

The Institut Mines-Télécom Chair, which was founded in 2013, is sponsored by Groupe Imprimerie Nationale, BNP Paribas, Orange, Dassault Systèmes, Deveryware and a partnership with the CNIL (the French Data Protection Agency). It is co-ordinated by Claire Levallois-Barth, a lecturer in law, and handles the legal, technical, economic, and philosophical aspects relating to the collection, use, and sharing of personal information.
cvpip.wp.mines-telecom.fr/home/ 

Engineering Studies: "Data Science" course

The Data Science course covers all areas related to the operation, management, and analysis of large volumes of structured and unstructured data. The professions of data scientist or data analyst, statistical engineer, and database administrator are examples of obvious openings, or the fields of research and R&D in statistical learning, data management, data extraction, data mining, and mathematics for learning. The course is divided into two branches with 6 common course units and 2 optional units. The optional units are Statistical Learning (at the intersection between computer science and mathematics) and Data Management (computer science).
enseignements.telecom-paristech.fr/programme.php?id=540&langue=EN 

Master 2 "Maths for big data science"

Co-accredited with the Ecole polytechnique and the first course at Master's level in Big Data involving several major academic players, this Research Master's is intended for an audience of students who wish to further their knowledge of applied mathematics in the field of Data Science, in relation to technological building blocks enabling "scalability." Aiming for a balance between mathematics and computer science, this Master's is also extremely practical through the case studies provided by companies.

Master 2 Computer Science: "Data & Knowledge" and "Data Scale" programmes

Télécom ParisTech participates in two programmes in the Master's in Computer Science at the Université Paris Saclay. The "Data & Knowledge" programme is entirely in English and allows students to join international companies and global leading research organisations. The "Data Management in a digital world" programme (DataScale) provides openings in the fields of industry, services, research, and R&D.

Post-Master's degree "Big Data: management and analysis of big data"

It is the first Advanced Master's in Big Data in France and is a specialised program which is aimed at graduates who are continuing their studies or retraining. It provides over 700 hours of lectures, practical work and seminars over a period of 16 months, as well as a project on a "common theme" which is supervised by a company. It finishes with a 4 - 6 month internship and defence of a professional thesis.
www.telecom-paristech.fr/formation-continue/masteres-specialises/big-data.html

Big Data Seminars

In addition to the Advanced Master and Master 2 in Mathematics, weekly seminars are offered every Thursday with specialist Big Data professionals: start-up, consultants, major groups, etc.

"Data Scientist" CES (Specialised Studies Certificate)

The CES provided by Télécom Évolution is intended for professionals who wish to increase their skills in the field of Data Science (storage, representation, statistical analysis, and visualisation). It is very active with 12 2-day sessions spread over a period of 10 months and the course aims to master the management and analytical techniques for Big Data and the key algorithms for Machine Learning.
www.telecom-bretagne.eu/formation-continue/formations-certifiantes/stage-fl9bd01-2015.php 

Short courses

Télécom Evolution  offers 8 short courses (1 or 2 days) focused on specific skills: infrastructures and distributed architectures, Data Science and Machine Learning, security, visualisation, the semantic web, data extraction, R language, etc. A module available to the general public over 2 days introduces non-specialists to the economic, legal, and technical issues of Big Data.
www.telecom-bretagne.eu/formation-continue/big-data/index-2015.php

MOOC "The essentials for Big Data"

This MOOC prepares people for attending courses in the field of Big Data. The targeted skills are an essential prerequisite in the fields of analysis, algebra, probabilities, statistics, Python programming and databases. The MOOC is made up of 7 parts and takes place over 6 weeks.
www.france-universite-numerique-mooc.fr/courses/MinesTelecom/04006/Trimestre_1_2015/about