[PDF] MSc IN DATA SCIENCES & BUSINESS ANALYTICS





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CENTRALESUPELEC

This elective course aims to provide CentraleSupélec students with basic knowledge in computer networking as well as a reasonable awareness of.



INTERNATIONAL MOBILITY PROGRAMMES

CentraleSupélec uses the European Credit Transfer System (ECTS). The course load at. CentraleSupélec is usually 30 ECTS per semester.



INTERNATIONAL MOBILITY PROGRAMMES

INCOMING Students : Double-Degree programmes (Centrale Paris & CentraleSupélec curriculum) : Ms. Marisol VERSTRAETE.



CENTRALESUPELEC

Description. Three successive courses help train students in programming and algorithmic. This course is the first one followed by two weeks of.



CentraleSupelec

02-Nov-2016 The courses of the Centrale Paris Engineering Curriculum at CentraleSupélec are taught in one of four language options specified for each ...



MSc IN DATA SCIENCES & BUSINESS ANALYTICS

CentraleSupélec is the result of the merger of the École Centrale Paris and Supélec in. January 2015. Since 2009



A NEW CAMPUS FOR CENTRALESUPELEC

09-Nov-2017 On September 11th the Parisian students of CentraleSupélec will discover two new buildings on the Saclay plateau



Presentation of International Fast Track CS V14

CentraleSupélec. Formerly Ecole Centrale Paris & Supélec. Accelerated degree in Engineering. – A post-graduate 2-year elite programme – 



CentraleSupelec Mobility Programs 2018

Discover our campuses & Access : http://www.centralesupelec.fr/en/our-campuses Double-Degree programs (Centrale Paris & CentraleSupélec curriculum) :.



CENTRALESUPELEC A GLOBAL HEI IN SCIENCES

Ecole Centrale Paris (Ecole Centrale Paris -1829). Supélec (Ecole Supérieure d'Electricité - 1894). Merged 1 Jan 2015 to jointly create CentraleSupélec.

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International

Rankings

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International

Rankings

Business Education

2016
#3

Master of Science

in Management #7

Master in Finance

#14

Executive Education

Programs

The digital revolution is currently transforming the world as we know it: disrupting all of our ingrained habits and opening up new domains of which we cannot yet grasp their full extent. Therefore, in this digital age, processing vast quantities of data has become a major issue for companies and for society as a whole. This digital frontier o?ers an incredible opportunity for young graduates who are in a unique position to blend technological, managerial and cross-cultural savoir-faire. In order to train the 'digital architects" who will be able to seize this opportunity, ESSEC and CentraleSupélec have joined forces to develop a radically original pro- gram: the MSc in Data Science & Business Analytics. This program is part of a major alliance between two world-renowned institutions, which share the same passion for excellence and a willingness to anticipate the needs and challenges of the future. With this program, we o?er ambitious students a unique experience thanks to the professors at our two institutions who are recognized for their expertise, their excellent research and in particular for their ability to build and transmit cutting-edge knowledfge. Becoming an MSc in Data Science & Business Analytics student will give you the chance to succeed in the rapidly evolving 21st century; in a world both complex and uncertain where the control of data becomes an invaluable asset to opening a number of doors.

Do you share our pifoneering vision?

Enroll in the ESSEC CentraleSupélec MSc in Data Sciences & Business Analytics program.

Prof. Jean-Michel uBlanquer

Dean and Presidenth, ESSEC Business Shchool

Hervé Biausser

Dean and Presidenth, CentraleSupélec

3

Message

from the Deans

The core of business decisionis

Society has entered a new digital era where the creation, consumption and use of digital content have changed our lives. The proliferation of sensors, the internet of things, digital services and communication continuously produce highly hete- rogeneous, highly unstructured and high dimensional data hardly interpretable from human intelligefnce. Reasoning from and mining this data constitutes a novel way to think out of the box, analyze, address unsolved problems and obtain new solutions. It is provides a wealth creation engine through the introduction of novel practices, services and policies. The future of business intelligence therefore relies jointly on mastering the science of data and the techniques of business analytics which have become the pillars of suchf interdisciplinary fe?orts. An intelligent use of data nowadays forms the core of business decisions and constitutes the driving force of the societal and economic evolution of the years to come. It is probably one of the most important topics of our days. Analysts estimate that data-related businesses generated about 10 billion dollars in recent years, and will probably generate more than 30 billion dollars in the years to come. The growth in job opportunities is tremendous: companies and organizations will need a couple of hundred thousand data scientists and business analytics lea- ders in the next few years. Moreover, the exponential growth in content genera- tion will bring about a huge need for highly qualified individuals with an in-depth knowledge and a global understanding of the technological and business challen- ges underlying thef digital evolutionf era. Recent business studies converge to an estimated need of educating several mil- lion data scientists and leaders within the decade to come. This is why two pres- tigious French Grafndes Ecoles ESSEC fBusiness School anfd CentraleSupélec have partnered to propose this very innovative and complete program. We believe that truly innovative leaders must be both business savvy and erudite in data sciences. Hence we propose a funique program wherfe students learn afnd combine the key skills in innovation and wealth creation that companies will increasingly require.

Guillaume Chevillon

Academic Co-DirectEor,

Professor of EconomEetrics

& Statistics,

ESSEC Business School

4

Nikos Paragios

Academic Co-DirectEor,

Professor of AppliEed

Mathematics

& Computer Science,

CentraleSupélec

An Alliance of excellience

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Niket, current student

• Awarded by 2 prestigious French

Grandes Ecoles

TAILORED TO INDIVIDUAL SNEEDS & GOALS

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From October to Decfember students mustf attend

six core courses. f vfhBa fhBMaé éfna fBss a Gf nefem fPrrPofCMéqJ uééf rhmBB-fhnNiMé Dealing with statistical methods for the analysis of multidimensional data, this course aims to develop analytical problem-solving skills while presenting quantitative methods apt to support decision-ma- king processes in the face of uncertainty. It also pro- vides actionable tools to analyze and leverage data (PCA, regressions, decision trees, clustering, data and text mining). This course aims to help students use quantitative techniques in a strategic consulting approach in order for them to be able to design, assess and manage bu- siness strategies. It is based on real life cases and will give students prerequisites on how to build a strategy and how to present it to di?erent types of audience and stakeholders. With a focus on forecasting methods used in business and economics, this course develops students" judg- ment and critical sense in order to be able to produce and evaluate operational forecasts by understanding how forecasting is possible, and how it can go wrong. These practical analytical skills will equip them with a competitive edge. :P PsihrmThmcs&FDcrTmccsuTP)v rhci-s usT10m)s4Pvs 1s 6rTo

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o Jean- rMic- hfhnNiMé mlaoroEaEBmmrBtc E m rhr€Crao Programming exercises in Python are covered in this course as well as the ba- sic theory and methods for the solution of optimization problems; iterative tech- niques for unconstrained minimization; linear and nonlinear programming as well as discrete methodsf for engineering apfplications. mDCt,ro m‚ Ccoroé An overview of the most important trends in machine learning, with a particular focus on statistical risk and its minimization with respect to a prediction function is given in this course. A substantial lab section involves group projects on data science competitions and gives students the ability to apply the course theory to real-world problems.f This course teaches about big data management - algorithms, techniques and tools needed to support big data processing - as storage, organization, and pro- cessing of data at a scale and e?ciency goes well beyond the capabilities of conventional informfation technologiesf. H , irintysi ncvakik yg qltl hnyignifk lai c::iaip lt tbi eigtalrihvourin nl.ovk

Massive Data Proceussing

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Geometric Methods iun Data Analytics

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Distributed Optimizuation & Computing

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Deep Learning & Counvolutional Networkus

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High Performance anud Parallel Computinug

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frt-PaPdC-adcmicosdPuafmComaedm,dfr, a, dC,edCee-aPPd-afa, d -a,ePdC,edfcCooa,iaPp Students can choose a curriculum that is balanced across both fields. They can also choose to Major in Data Sciences or Business Analytics by validating four elective courses in uthis field.

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