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Study MSc Data Science

Fees, Modules, Entry Requirements & Application for Bangladeshi Students

Quick View

  • Study Option
    Full-Time
  • Intakes
    September, February
  • Location
    Main Campus, Debrecen, Hungary
  • Duration
    4 Semesters
  • Level
  • Subject
  • International Fees
    $ 7,500 per year
    Up to 50% of tuition fees scholarships

How to Apply

Before making an application, you will need to decide on your course and learn requirements clearly. Information in this page is available for the international students only.

Apply Now

The MSc Data Science at the University of Debrecen is a full-time 4 Semesters Postgraduate program in the field of Computing & Cybersecurity. Delivered at the University's Main Campus campus in Debrecen, Hungary, the course offers a balanced mix of academic study and practical experience.

Ideal for Bangladeshi students and other international applicants, this program provides high-quality education at a yearly competitive international tuition fee of $ 7,500 Starting each September, February, it is designed to equip students with essential skills for advanced study and professional growth.

The University of Debrecen offers modern facilities and a supportive environment, ensuring international students receive the guidance and resources needed for success. With a welcoming campus community and dedicated support services, Bangladeshi students can confidently plan their study abroad journey in the Hungary through this program.

Course Highlights

The aim of the program is to train professionals who can understand the properties of different types of data and the structure of complex data sets, unfold the relationships inherent in the data, apply the necessary transformations to raw data to prepare it for analysis, analyze data, draw conclusions from the data, and model real-world processes. They will also be able to develop and manage data-oriented applications, perform and coordinate R&D tasks and continue their studies in PhD programs.

Course Modules

Information Security 6 Credits
Fundamentals of Machine Learning 6 Credits
Statistics for Data Science 6 Credits
Cloud Computing 6 Credits
Data Visualization Methods 3 Credits
Programming for Data Science 3 Credits
Optimization for Data Science 6 Credits
Data Ethics 3 Credits
Advanced Natural Language Processing 6 Credits
Docker and Kubernetes in ML 6 Credits
Geometric Data Analysis 3 Credits
Processing Large Amounts of Sensor Data 3 Credits
Clinical Big Data 6 Credits
Thesis 1 15 Credits
Thesis 2 15 Credits
Social and Technological Networks 6 Credits
Modern Deep Learning Frameworks 3 Credits
Generative Networks 3 Credits
Extreme Computing 6 Credits
Design of Big Data Systems 6 Credits
Big Data Technologies 3 Credits
Advanced Robotics 6 Credits
Autonomous Vehicles 6 Credits
Theoretical and Neural Models in the Industry 6 Credits
Parallel Computing with CUDA 3 Credits
Cryptography 6 Credits
AI Security 6 Credits
Time Series Analysis 6 Credits
Financial Modelling 6 Credits
Stochastic Data Mining 6 Credits
Genetics and Big Data 6 Credits
Professional Training 9 Credits
Advanced Machine Learning 6 Credits
Advanced Reinforcement Learning 6 Credits
Secure Coding 6 Credits

Learning Structure

  • Lecture, seminar: 40%
  • Practice: 60%

Entry Requirements

  • A second class Bacheor degree in computing or a relevant information technology discipline.

English Language Requirements

IELTS  Overall 6.0

Listening

5.5

Reading

5.5

Writing

5.5

Speaking

5.5
Language Accepts: IELTS, TOEFL
No IELTS? No problem!
Got TOEFL, PTE, Duolingo, LanguageCert or OIETC? Instantly check your IELTS equivalency and see if you qualify for your dream university!

Documentary Evidence List

  • Bachelor's Transcripts
  • Degree Certificate
  • English Test (IELTS/ TOEFL)
  • Motivation Letter/ SOP
  • 2 Recommendation Letters
  • Updated CV/ Resume
  • Work Experience Certificates (if study gap)
  • Passport Copy

Study Gaps

For applicants with an academic or professional gap of up to 5 years, admission is generally considered acceptable. If the gap exceeds this period, applications may still be successful but will typically be assessed on a case-by-case basis.

To strengthen your profile, it is important to:

  • Provide a clear explanation of how you spent the gap period (e.g., employment, further learning, personal responsibilities).
  • Emphasize the skills and experiences you developed during this time that are relevant to the program.
  • Demonstrate that your academic qualifications continue to meet the course entry requirements.

Disclaimer: The information provided on this page is sourced from the official university website. Please note that universities may update their course details, fees, entry requirements and any other related information at any time without prior notice. We recommend verifying the latest updates directly with the university.

Last reviewed on 10 October 2025.

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