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Tuition EUR 8,000 (Tuition (Year)) — International students; EUR 8,000 (Tuition (Year)) — EU/EEA students
Degree Master
Duration 12 months
Deadline 2031-05-18
Delivery On-campus
Location Rennes, France
Language English

Program Overview

The Statistics for Smart Data at ENSAI - National School for Statistics and Information Analysis is a Master programme in Computer Science & IT over 12 months, delivered On-campus. This programme equips graduates with advanced knowledge and practical skills for professional and academic careers in the field.

Students gain a rigorous grounding in both the theoretical foundations and applied dimensions of computer science & it. The programme combines coursework, research components, and practical projects that develop critical thinking, problem-solving, and specialist expertise relevant to industry and research needs.

Graduates of the Statistics for Smart Data programme are well-prepared for careers in academia, industry, government, and the private sector across France and internationally. The programme provides an internationally recognised qualification within the Bologna higher education framework.

Key Program Features

  1. Duration: 12 months
  2. Language of instruction: English
  3. Study mode: On-campus
  4. Tuition: EUR 8,000 (Tuition (Year)) — International students; EUR 8,000 (Tuition (Year)) — EU/EEA students
  5. Location: Bruz, France

Career Opportunities

Graduates of the Statistics for Smart Data programme are prepared for diverse careers in computer science & it:

  1. Software Engineer / Developer
  2. Data Scientist
  3. Machine Learning Engineer
  4. IT Project Manager
  5. Cybersecurity Analyst
  6. Cloud Solutions Architect

Program Curriculum

Detailed curriculum information is not available. Please check the university website or contact them directly for the most up-to-date course information.

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Admission Requirements

Academic Requirements

The Master of Science in Statistics for Smart Data \xc2\xa0is 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 statistical, mathematical and computer science background is required. For more detailed information about prerequisite knowledge, click on the categories below: (insert new links)

  • Analysis
  • Algebra
  • Probability and Statistics
  • Programming

Candidates with degrees from non-EU countries must provide GRE revised General Test results or equivalent such as GMAT, TAGE MAGE, etc. Please have results sent directly to ENSAI by using the following Designated Institution code when registering: 7180.\xc2\xa0

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.\xc2\xa0

Applications are selected based on candidates\' degrees, level, and skills. A personal interview (in person or via videoconference) will be at the discretion of the ENSAI admissions committee.

Tuition & Financial Information

Tuition Fee

EUR 8,000 (Tuition (Year)) — International students; EUR 8,000 (Tuition (Year)) — EU/EEA students

Tuition fees: EUR 8,000 (Tuition (Year)) — International students; EUR 8,000 (Tuition (Year)) — EU/EEA students

Financial Aid & Scholarships

Contact ENSAI - National School for Statistics and Information Analysis directly for scholarship, grant, and financial aid information for this programme. Many European universities offer merit-based and need-based funding for international and domestic students.

About ENSAI - National School for Statistics and Information Analysis

ENSAI - National School for Statistics and Information Analysis logo

ENSAI - National School for Statistics and Information Analysis

Rennes, France

Visit the university profile page to learn more about this institution.

University Profile
  • Application Deadline 2031-05-18
  • Start Date 2018-09-15
  • Language English
  • Duration 12 months
  • Credits 240