Master Year 2 Data Science
Program information will be updated when admission opens.
| Year | Master Year 2 |
| Program | Data Science |
| ECTS Credits | 60 |
| Language | English and French |
| Orientation | Research and Industry |
| Location | Palaiseau Campus |
| Course duration | 12 months, full time |
| Course start | September |
| Degree awarded | Master’s degree |
WHY ENROLL IN THIS PROGRAM?
Asset n° 1
Master key tools and skills for data scientists based on an interdisciplinary approach
Asset n°2
Lay the foundations of your future career by pursuing a PhD track in Data Science (link to PhD track Data Science) or following an apprenticeship program
Asset n°3
Open up numerous job opportunities in the context of a global shortage of data scientists and data analysts
Today, major players in the world of business are increasingly aware of the potential of their data and are looking for ways to extract as much useful information as possible. Data scientists are in charge of retrieving, storing, organizing, processing this mass of information to create value. This is a hybrid profile requiring a solid background in mathematics and statistics, mastery of data management and processing tools and infrastructure, as well as curiosity and a thirst to understand.
Exploiting this immense volume of data requires sophisticated mathematical techniques, which form the basis of Data Science. This transition from data to knowledge brings many challenges that require an interdisciplinary approach. Data Science relies heavily on the statistical processing of information: mathematical statistics, numerical statistics, statistical learning and machine learning.
A wide range of mathematical and numerical statistics and learning methods are used from analyzing exploratory data to sophisticated inference techniques (hierarchical graphical models) and classification or regression (deep learning, support vector machine). In order to be develop on a massive scale, these methods require the mastery of data distribution mechanisms and large-scale calculations. Applied mathematics (functional analysis, numerical analysis, convex and non-convex optimization) also plays an essential role.
Objectives
This program allows students to:
- Become the data scientists of tomorrow both in academia and industry - a large proportion of our students choose to pursue doctorate studies
- Master sophisticated mathematical techniques to extract relevant information: statistical processing of information, analysis of exploratory data, techniques of inference and classification or regression, data distribution mechanisms and very large-scale calculations
Data Science has a strong impact on many sectors. There is currently a large worldwide shortage of data scientists and data analysts. Students from Data Science and Big Data courses are therefore eagerly awaited on the global job market. Like all fields of breakthrough innovation (e.g. biotechnology and e-medicine), there is a high need for high-level engineers and doctoral candidates.
Course details will be available when admission opens.
Admission requirements
Academic prerequisites
Completion of the first year of a Master in mathematics at Institut Polytechnique de Paris or equivalent in France or abroad.
Language prerequisites
- English
- French
How to apply
Applications can be submitted exclusively online. You will need to provide the following documents:
- Transcript
- Two academic references (added online directly by your referees)
- CV/resume
- Statement of purpose
You will receive an answer in your candidate space within 2 months of the closing date for the application session.
Fees and scholarships
Tuition fees will be communicated when admission opens.
Find out more about scholarships
Applications and admission dates
Coordinator
Program office
General enquiries
Today, major players in the world of business are increasingly aware of the potential of their data and are looking for ways to extract as much useful information as possible. Data scientists are in charge of retrieving, storing, organizing, processing this mass of information to create value. This is a hybrid profile requiring a solid background in mathematics and statistics, mastery of data management and processing tools and infrastructure, as well as curiosity and a thirst to understand.
Exploiting this immense volume of data requires sophisticated mathematical techniques, which form the basis of Data Science. This transition from data to knowledge brings many challenges that require an interdisciplinary approach. Data Science relies heavily on the statistical processing of information: mathematical statistics, numerical statistics, statistical learning and machine learning.
A wide range of mathematical and numerical statistics and learning methods are used from analyzing exploratory data to sophisticated inference techniques (hierarchical graphical models) and classification or regression (deep learning, support vector machine). In order to be develop on a massive scale, these methods require the mastery of data distribution mechanisms and large-scale calculations. Applied mathematics (functional analysis, numerical analysis, convex and non-convex optimization) also plays an essential role.
Objectives
This program allows students to:
- Become the data scientists of tomorrow both in academia and industry - a large proportion of our students choose to pursue doctorate studies
- Master sophisticated mathematical techniques to extract relevant information: statistical processing of information, analysis of exploratory data, techniques of inference and classification or regression, data distribution mechanisms and very large-scale calculations
Data Science has a strong impact on many sectors. There is currently a large worldwide shortage of data scientists and data analysts. Students from Data Science and Big Data courses are therefore eagerly awaited on the global job market. Like all fields of breakthrough innovation (e.g. biotechnology and e-medicine), there is a high need for high-level engineers and doctoral candidates.
Course details will be available when admission opens.
Admission requirements
Academic prerequisites
Completion of the first year of a Master in mathematics at Institut Polytechnique de Paris or equivalent in France or abroad.
Language prerequisites
- English
- French
How to apply
Applications can be submitted exclusively online. You will need to provide the following documents:
- Transcript
- Two academic references (added online directly by your referees)
- CV/resume
- Statement of purpose
You will receive an answer in your candidate space within 2 months of the closing date for the application session.
Fees and scholarships
Tuition fees will be communicated when admission opens.
Find out more about scholarships