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Master’s Degree in Data Science & Big Data
The Master’s Degree in Data Science & Big Data trains experts capable of collecting,
analyzing, and leveraging massive datasets from businesses, connected devices, and
social networks.
This program combines advanced computer science, applied mathematics, and data
mining tools to transform raw information into strategic insights.
It emphasizes not only technical mastery, but also ethical considerations, data
protection (GDPR), and sustainable innovation.
Through a curriculum blending courses, real-world case studies, and recognized
certifications, students quickly become operational and ready to meet the needs of
companies undergoing digital transformation.
Key Information
Degree:
National Master’s Degree
Credits:
120 ECTS
Language of Instruction:
French (with some modules taught in English)
Format:
Full-time or Work-Study
Admission Level:
Bac+3 (Bachelor’s) / Bac+4 (Equivalent)
Key Information
Degree:
National Master’s Degree
Credits:
120 ECTS
Admission Level:
Bac+3 (Bachelor’s) / Bac+4 (Equivalent)
Format:
Full-time or Work-Study
Why Choose This Program?
- A future-proof program addressing the global demand for Data Science and Big Data specialists.
- Practical learning based on real business case studies and professional simulations.
- Recognized certifications included (Cisco DevNet, Python PCAP, Microsoft, IBM, Tableau…).
- Strong international exposure through mobility programs, dual degrees, and internships abroad.
A Globally Oriented Program
In a field as universal as Data Science, international exposure is essential. Thanks to
Leaders University’s academic and professional partnerships, students benefit from
multiple global opportunities:
- Dual Degree
Access to specialized master’s programs in Data Science at partner universities.
- Academic Mobility
Possibility to complete the second year abroad at renowned
institutions.
- International Internships
Immersive experiences in companies, startups, or research
centers in Europe and beyond.
- Global Network
Participation in international seminars, workshops, and competitions
in Data Science & AI.
Learning Objectives
- Master Big Data tools and technologies
- Analyze and interpret large-scale datasets
- Develop decision-support solutions
- Design and optimize complex data-driven systems
- Integrate ethical considerations and GDPR compliance
- Innovate through the strategic use of data
Teaching Methods
The program is based on an active and professional-oriented pedagogy, designed to prepare students for the realities of the profession:
- Interactive courses and tutorials
- Real-world business case studies
- Group projects and data challenges
- Mandatory professional internships
- Technical certifications (Cisco, Python, etc.)
- Seminars with international experts
Career Opportunities
Short-Term Careers
Graduates can quickly enter the job market in technical and analytical positions such as:
- Data Analyst
- Business Intelligence Developer
- Junior Big Data Engineer
- Applied Statistics Analyst
- Applied Statistics AnalystDecision-Support Solutions Developer
- Information Systems Consultant
Medium-Term Careers
Avec de l’expérience et des compétences consolidées, les perspectives évoluent vers des postes
stratégiques et de management :
- Data Scientist
- Business Intelligence Manager
- Big Data Architect
- Data Strategy & Analytics Manager
- Senior Digital Transformation Consultant
- Chief Data Officer (CDO)
International Outlook & Opportunities Abroad
In a field as global as Data Science, internationalization is a major asset. Students
benefit from a strong network of partnerships that opens doors to:
- Dual Degrees: Specialized programs in Data Science and Artificial Intelligence.
- Mobility in M2: Possibility to complete the second year at a leading international institution.
- International Internships: Placements in companies, startups, or research labs abroad.
- Academic Exchanges: Participation in workshops, conferences, and international hackathons in Big Data & AI.
Admission Requirements
Admission to M1:
Open to holders of a Bachelor’s degree in Computer Science, Applied Mathematics, Statistics, or related technological fields.
Admission to M2:
Reserved for students who have completed M1 in Data Science, Big Data, or Computer Science at Leaders University or an equivalent institution, subject to academic committee approval.
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