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Academics

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Master of Science in Data Science

The program is aligned with the best- practices of the world’s leading programs, combining a thorough coverage of the fundamentals with innovative applications in a wide range of subject areas. The MSDS program will provide an in-depth education in Data Science, incorporating fundamental concepts from disciplines such as Computer Science, Mathematics, Physics, Robotics, and related engineering fields.

The first term of study is designed to provide a foundation of the field, and immerse the students in the main topics and skills required to succeed in the program. Terms two and three will develop advanced areas of specialization, and produce a thesis project that uses real-world data for practical purposes, ideally aligned with the development priorities of the country. The final term focuses on the completion and documentation of the thesis project. 

The program offers a research-and student-centered education. The balance of emphasis on fundamentals, recent computational innovations, big data analytics, and applied artificial intelligence will stimulate and accelerate knowledge discoveries. The program requires a 30 ECTS thesis  as part of the degree completion requirements. Students are encouraged to present their research findings at international conferences and to publish their results in scientific journals.

More information is available on the NU SEDS website: https://seds.nu.edu.kz/msc_in_ds

 

General information: 

Campus: Astana, Kazakhstan

Language: English

Delivery mode: Full-time, on-campus

Duration: 2 years

Total ECTS credit: 120

 

Courses

  • Discipline Core (6) (36 ECTS)
  • CSCI 501 Fundamentals of Data Science – I (6 ECTS)
  • CSCI 502 Fundamentals of Data Science – II (6 ECTS)
  • CSCI 504 Data Mining and Decision Support (6 ECTS)
  • CSCI 507 Database Management Systems (6 ECTS)
  • MATH 540 Statistical Analysis (6 ECTS)
  • CSCI 545 Big Data Analytics (6 ECTS)
  • Innovation Pillar (18 ECTS)
  • CSCI 551 Process and Project Management (6 ECTS)
  • SST 504 Innovation and Entrepreneurship (6 ECTS)
  • CSCI 552 Data-Driven Innovation (6 ECTS)   Electives (18 ECTS)
  • CSCI 506 Big Data File Structures and NoSQL 
  • Databases (6 ECTS)
  • CSCI 508 Machine Learning (6 ECTS)
  • CSCI 578 Data Security and Protection (6 ECTS)
  • CSCI 580 Information Retrieval (6 ECTS)
  • MATH 541 Data Analysis and Statistical Learning 
  • CSCI 581 Knowledge Engineering (6 ECTS)
  • BIOL 580 Applied Bioinformatics (6 ECTS)
  • CSCI 584 Deep Learning (6 ECTS)
  • CSCI 585 Statistical Methods in Natural Language 
  • Processing (6 ECTS)
  • CSCI 587 Social Media Analytics (6 ECTS)

 

Career

Graduates of the program might find jobs in following areas:

• Statistician

• Business intelligence reporting professional

• Data Analyst

• Data Mining or Big Data Engineer

• Program/Project Manager



Admission requirements
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