Master Year 1 High Performance Data Analytics
| Year | Master Year 1 |
| Program | High Performance Data Analytics |
| ECTS Credits | 60 |
| Language | French, English |
| Orientation | Research |
| Location | Palaiseau Campus |
| Course duration | 12 months, full time |
| Course start | September |
| Degree awarded | Master’s degree obtained on completion of a second year of Master |
WHY ENROLL IN THIS PROGRAM?
Asset n° 1
Prepare for a PhD
Asset n°2
Acquire solid core knowledge in the field of data analytics
Asset n°3
Follow specific research seminars and conduct research projects
The rapid growth of the internet has led to vast amounts of data being collected. As analyzing this data requires tremendous computing power, high-performance data analytics employs various parallelization techniques to reduce the execution time. These techniques can be applied to various domains such as high-performance computing, artificial intelligence and big data.
The two-year High Performance Data Analytics Master’s program covers the full software stack of high-performance data analytics applications available today, from operating systems and the foundations of parallel programming to high-performance computing applications and AI techniques. The program comprises mandatory courses focusing on core topics like operating systems and parallel programming, as well as optional courses addressing either HPC applications (numerical simulation and modeling) or AI applications (machine learning and data mining). The program focuses on research and introduces students to research labs through projects and a Master’s thesis, preparing the way for further PhD studies.
Objectives
This two-year Master’s program enables students to:
- Master the foundations of parallel computing for analyzing massive amounts of data
- Acquire core knowledge in architecture, operating systems, parallel programming, as well as an overview of domain applications such as high-performance computing, artificial intelligence and big data
- Gain advanced knowledge in a specific application
- Develop the skills required to pursue a research career through seminars and projects
On completing the two-year program, students will be equipped to:
- Pursue a PhD in Computer Science at Institut Polytechnique de Paris or at another highly ranked university
- Join the R&D departments of an innovative IT company
The Master HPDA is a two years program. All Its courses can be taken during Year 1 or Year 2.
Core courses
|
Elective courses
|
Core courses
|
M1 research project |
20 ECTS English |
Elective courses
|
Operating systems |
45h 5 ECTS English |
|
High performance runtimes |
45h 5 ECTS English |
|
Compilation |
45h 5 ECTS English |
|
Systems for big data |
45h 5 ECTS English |
|
Machine learning 2 |
45h 5 ECTS English |
|
Effective implementation of the finite element method |
45h 5 ECTS English |
Admission requirements
Academic prerequisites
- Completion of a Bachelor of Computer Science or Applied Mathematics at Institut Polytechnique de Paris or equivalent in France or abroad
- Have an outstanding academic record
Language prerequisites
- French
- English
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
Estimated fees for 2022-2023 are subject to increase
- EU/EEA/Switzerland students: 243€
- Non-EU/EEA/Switzerland students: 3770€
- Engineer students enrolled in one of the five member schools of Institut Polytechnique de Paris (Ecole polytechnique, ENSTA Paris, ENSAE Paris, Télécom Paris and Télécom SudParis): 159€
- Special cases: please refer to the "Cost of studies" section of the FAQs
Find out more about scholarships
Applications and admission dates
Coordinator
Program office
General enquiries
The rapid growth of the internet has led to vast amounts of data being collected. As analyzing this data requires tremendous computing power, high-performance data analytics employs various parallelization techniques to reduce the execution time. These techniques can be applied to various domains such as high-performance computing, artificial intelligence and big data.
The two-year High Performance Data Analytics Master’s program covers the full software stack of high-performance data analytics applications available today, from operating systems and the foundations of parallel programming to high-performance computing applications and AI techniques. The program comprises mandatory courses focusing on core topics like operating systems and parallel programming, as well as optional courses addressing either HPC applications (numerical simulation and modeling) or AI applications (machine learning and data mining). The program focuses on research and introduces students to research labs through projects and a Master’s thesis, preparing the way for further PhD studies.
Objectives
This two-year Master’s program enables students to:
- Master the foundations of parallel computing for analyzing massive amounts of data
- Acquire core knowledge in architecture, operating systems, parallel programming, as well as an overview of domain applications such as high-performance computing, artificial intelligence and big data
- Gain advanced knowledge in a specific application
- Develop the skills required to pursue a research career through seminars and projects
On completing the two-year program, students will be equipped to:
- Pursue a PhD in Computer Science at Institut Polytechnique de Paris or at another highly ranked university
- Join the R&D departments of an innovative IT company
The Master HPDA is a two years program. All Its courses can be taken during Year 1 or Year 2.
Core courses
|
Elective courses
|
Core courses
|
M1 research project |
20 ECTS English |
Elective courses
|
Operating systems |
45h 5 ECTS English |
|
High performance runtimes |
45h 5 ECTS English |
|
Compilation |
45h 5 ECTS English |
|
Systems for big data |
45h 5 ECTS English |
|
Machine learning 2 |
45h 5 ECTS English |
|
Effective implementation of the finite element method |
45h 5 ECTS English |
Admission requirements
Academic prerequisites
- Completion of a Bachelor of Computer Science or Applied Mathematics at Institut Polytechnique de Paris or equivalent in France or abroad
- Have an outstanding academic record
Language prerequisites
- French
- English
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
Estimated fees for 2022-2023 are subject to increase
- EU/EEA/Switzerland students: 243€
- Non-EU/EEA/Switzerland students: 3770€
- Engineer students enrolled in one of the five member schools of Institut Polytechnique de Paris (Ecole polytechnique, ENSTA Paris, ENSAE Paris, Télécom Paris and Télécom SudParis): 159€
- Special cases: please refer to the "Cost of studies" section of the FAQs
Find out more about scholarships