Master of Science in Data Science and Artificial Intelligence
Transform raw data into actionable insights using cutting-edge machine learning and AI techniques.
Best for:Best for graduates with a BSc in Computer Science, Mathematics, Physics, or related fields who want to specialize in AI and data science with hands-on programming and research-focused applications.
Overview
This Master’s programme at Radboud University in Nijmegen, Netherlands, equips students with advanced skills in data science and AI to solve complex problems across industries and research. The curriculum blends core courses in machine learning, probabilistic modeling, and information retrieval with specialized tracks in natural language processing, medical pattern recognition, neuroimaging, and bioinformatics. Students are expected to develop both technical proficiency and creative problem-solving abilities, enabling them to design and implement their own AI solutions. The programme emphasizes hands-on programming and practical applications, preparing graduates for careers in academia, industry, or research. Ideal for those with a strong computational background seeking to specialize in AI-driven data analysis.
What you'll do
- Develop and implement machine learning models and AI algorithms to solve real-world problems.
- Conduct research in specialized areas such as natural language processing, medical imaging, or bioinformatics.
- Design and execute data-driven projects using advanced programming languages and tools.
- Analyze and interpret complex datasets to derive meaningful insights and solutions.
- Collaborate with peers and faculty on interdisciplinary research projects.
- Apply probabilistic modeling techniques to enhance data analysis and decision-making processes.
Requirements
Degree required: Bachelor of Science in Computer Science, Mathematics, Physics, or a related quantitative field
Degree offered: Master of Science
Language: English; proficiency sufficient for academic study and research
Instruction: English
- Proficiency in programming languages such as Python, R, or Java
- Strong background in mathematics and statistics
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
- Familiarity with data structures and algorithms
- Basic understanding of databases and data management
- Open to international applicants
- No specific age or residency restrictions
- Prior academic performance and motivation are key selection criteria
Funding & terms
Programme and admissions
Admissions not verified
A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.
- Intake
- Not confirmed by the source
- Duration
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- Teaching language
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- Taught / research mode
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- Study mode
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- Campus
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- Prerequisites
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- Application instructions
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- Tuition
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- Funding
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How to apply
Deadline: 2027-04-01
Applicants must submit their application through Radboud University’s official online portal. Required documents include a CV, a motivation letter, academic transcripts, a passport-sized photo, and proof of English proficiency. Additional documents may be requested depending on the applicant’s background.
- CV
- Motivation letter
- Academic transcripts (BSc)
- Passport-sized photo
- Proof of English proficiency (e.g., IELTS, TOEFL)
- Reference letters (if required)
Contact
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.