MSc in Big Data
Big Data at ENSAI
The demand for skills in the field of high-dimensional data processing, otherwise known as Big Data, is increasing dramatically worldwide, yet serious academic programs for this domain are still quite rare.
ENSAI is currently the only French engineering school accredited to offer an all-English program with this unique training, combining Statistics and Computer Science. ENSAI is accredited by the French Ministry of Higher Education and Research to deliver a Master of Science in Big Data (known as a Master international or DNM in the French nomenclature).
ENSAI has many years of experience dispensing multidisciplinary training (Statistics, Computer Science, and Econometrics), numerous international corporate and academic partnerships, a Big Data Academic Platform established by GENES, and a Big Data research chair financed by the Institut Louis Bachelier and the Fondation du Risque.
ENSAI's Master of Science in Big Data meets the very important needs of corporations and organizations of all kinds for graduate-level training that is nearly non-existent in academic offerings on the French, European, and international scale.
The structure of this Master's program is composed of 2 semesters of coursework at ENSAI, followed by an internship within the professional world or academia/research laboratories.
Since this program welcomes students with varying academic levels and skills in Computer Science, Mathematics, and Statistics, the structure aims to bring all students to the same scientific level in all three fields, with respect to their existing training, knowledge, and skills.
Therefore, in addition to common courses, the first semester includes courses tailored for students with different profiles. These courses take the form of two different tracks: Computer Science and Statistics, where students study the courses in which they need more training.
Note: In order to permanently ensure that the curriculum is adapted for the needs of the current job market, ENSAI reserves the right to make slight changes to the proposed curriculum and the descriptions between the period of admission and the start of the academic year.
Learning about Big Data is a hands-on experience. ENSAI has invested heavily to ensure that its Big Data students have the best technology at their fingertips. To learn more about the specifics of what is available to students enrolled in the Big Data degree, consult the list of resources provided below.
Graduates of the program are skilled Data Scientists. In addition to doctoral possibilities in research, they will have numerous career opportunities in international corporations and data start-ups in the following areas:
- Digital Marketing
- Business Analytics
- Risk Management
- Yield Management
- Industrial applications
- Supply and distribution
- Healthcare industry
- Social networks analysis
- Research and development in scientific domains
- Software industry
All courses and examinations occur in English. Non-English speakers must have a minimum level of B2 (CEFR scale). Certificates requested with application form.
Non-French speakers benefit from intensive French courses the preceding summer (July and August), as well as weekly evening French classes during the academic year.
Foreign French-speaking students possessing an official French language certificate (DELF or DALF) may request to be exempted from some or all of the French courses. Students possessing French nationality are automatically exempted.
See below for program cost details.
This final phase of the MSc in Big Data program involves a five-month paid internship, which can take place either in France or abroad, in either the professional world or academic/research laboratories. This experience should allow for the student to apply the statistical and computer science theory and methods that they have learned during the two semesters of coursework.
The student must write an Internship Report and defend it in front of a jury the following Autumn.
The MSc in Big Data program cost is fixed at:
- €8,000* for normal tuition, inclusive of all fees and registration
- €10,000 for professionals, corporations, and organizations (financing current employees, over 1-2 years, in context of Continuing Education)
*Reduced tuition possible for students from Academic Partner Institutions
Students following this Master's program are not eligible to apply for GENES' student grant based on financial need.
Université d'été (Intensive French Summer Program):
Non-French speakers also pay €2,000 for the 2-month Intensive French Summer Program (July and August): the Université d'été; this cost is inclusive of courses and program fees. This is made payable to the organizing service at CIREFE (not ENSAI) directly upon arrival. Participants have 2 options for accommodation and choose when registering for the Université d'été program:
- living with a French host family (cost: €26/night = €182/week + one time €6 application fee)
- living in a university residence hall (renovated room with private bathroom, shared kitchen) (cost: €238,75/month)
The Master of Science in Big Data is open to students of all nationalities.
All applicants must have a minimum of 4 years of higher education (at least a 4-year Bachelor's degree or the first year of a Master's). A strong mathematical and computer science background is required. For more detailed information about prerequisite knowledge, click on the categories below:
Candidates with degrees from non-EU countries must provide GRE revised General Test results. Please have results sent directly to ENSAI by using the following Designated Institution code when registering: 7180. For more information about the GRE, please visit the official website: http://www.ets.org/gre
Non-native English speakers will be required to certify a minimum B2 (CEFR) level of English by providing valid results from a recognized language certification such as the TOEIC, TOEFL, IELTS, CLES, etc.
Applications are selected based on candidates' degrees, level, and skills. A personal interview (in person or via videoconference) will be at the discretion of ENSAI.