Contexte
In today’s transforming and competitive world, companies strive to stay ahead of the market and make the best informed business decisions. Investing in the innovative technology has become a necessity.
Collecting and analyzing data in real-time help companies determine new market trends. By investing and implementing big data systems, they get new insights to build a more responsive and effective business, reach a higher level of performance and unlock new market opportunities while monitoring their risks.
Companies who are looking to capitalize on data science and set up successful big data strategies have 3 challenges to face:
1/ a technological challenge: collecting and storing the data pool, dealing with the spread of vast amounts of information that is often very disorganized (IP addresses, fingerprinting, website logs, static web or warehouse data, social media, etc.).
2/ a scientific challenge: structuring and dissecting the data, uncovering knowledge from these data through different scientific tools like data visualization.
3/ an economic challenge: understanding and interpreting the data, taking advantage of them to gain insight and boost the competitivity to the next level. Data are becoming part of business level strategies: they help companies improving their decision-making processes, implementing predictive analysis on emerging markets and measuring risk before entering new segments.
Objectif
Ecole Polytechnique and our partner business school HEC Paris offer a two-year joint graduate degree program in “Data Science for Business”. It aims at training students in data sciences and provides them with high-level skills on technological, scientific, strategic and business levels. Our association represents the best Engineering & Business combination Europe could possibly offer, particularly in the field of Data Science and Business.contenu
The program combines a scientific and a business approach to contemporary Data Science issues and challenges. The first year is spent at Ecole Polytechnique, with a strong focus on scientific and mathematic topics. The second year is spent at HEC Business School, where students are provided with the knowledge and skills in the business field. During these two years, students benefit from world class faculty and work with leading data scientists in specialized research units and a competitive environment.domaines d'enseignement
Mathématiques appliquées.compétences acquises
The MSc Data Science for Business will provide you with the fundamental skills and understanding of Data issues and challenges. This program responds specifically to the growing demand by companies for a new generation of data scientists and managers, who can deal with data pool on technological, scientific and business levels.métiers
- Financial, banking and insurance sector (BNP Paribas, Société Générale, Barclays, HSBC, AXA).
- Telecommunications and digital (Orange, IBM, Google, Facebook, Criteo, start-ups).
- Manufacturing IT industry.
- E-commerce and retail companies (Amazon, FNAC, Darty, Cdiscount…).
- Consultancy agencies (McKinsey, Accenture, Cap Gemini…) and Business Intelligence (Keyris, Sopra Group, CapGemini, SAP-Business Object, SAS).
- Data-driven marketing industry.
- Media and the leisure industry.
débouchés
- Financial, banking and insurance sector (BNP Paribas, Société Générale, Barclays, HSBC, AXA).
- Telecommunications and digital (Orange, IBM, Google, Facebook, Criteo, start-ups).
- Manufacturing IT industry.
- E-commerce and retail companies (Amazon, FNAC, Darty, Cdiscount…).
- Consultancy agencies (McKinsey, Accenture, Cap Gemini…) and Business Intelligence (Keyris, Sopra Group, CapGemini, SAP-Business Object, SAS).
- Data-driven marketing industry.
- Media and the leisure industry.
Parcours
- GD-DSB-GD1 Data Science for Business - Graduate Degree 1A
- GD-DSB-S1 GD DSB - Semestre 1
- HFC552 Aspects of Comparative Commercial Law
- MAP530 Probabilty Refresher Course
- MAP532 Mathematical Foundations of Data Science
- MAP531 Statistics
- MAP534 Introduction to Machine Learning
- MAP535 Regression
- MAP536R R for Data Science
- MAP536P Python for Data Science
- HFC551 The Myth of Paris (1830-Present)
- HFC555 Economic Sociology
- HFC556 Introduction to French Politics
- HFC557 Introduction to Political Philosophy: Philosophy of Work
- HFC558 EU Governance and Policies: Focus on Research and Innovation, and International Cooperation and Development
- HFC553 Topics in Science, Technology, and Society
- MAP658 Times Series Financial Data
- GD-DSB-S2 GD DSB - Semestre 2
- HFC564 Sociology of Energy Transitions: Innovation, Socio-technical Change and Controversies in the Energy Sector
- MAP540 Data Camp Project
- MAP541 Advanced Machine Learning
- MAP543 Database Management II
- MAP546 Statistics in Action
- MAP537 Quantitative Marketing
- SPO502 Sports - 502
- HFC561 Introduction to French Cinema
- HFC566 Introduction to French Politics
- HFC567 Introduction to Political Philosophy: Philosophy of Work
- HFC569 Philosophy of Science Fiction
- HFC563 Multicultural France
- MAP596A Internship for Data Science for Business (X)
- MAP596B Internship for Data Science for Business
- French Français
- English English
- GD-DSB-S1 GD DSB - Semestre 1
- GD-DSB-GD2 Data Science for Business - Graduate Degree 2A
- GD-DSB-S3 GD DSB - Semestre 3
- GD-DSB-S4 GD DSB - Semestre 4
- PHY101 Physics I: Mechanics and Heat