Masters (MS) in Data Science Abroad


Computer Science is the study of theory, engineering, experimentation that form the basis for the design and effectiveness of computers. It involves the study of algorithms and their application in the real world. Computer Science can be defined as the study of automating algorithmic processes that scale. It is the scientific and practical approach to computation and its applications and the systematic study of the feasibility, structure, expression, and mechanization of the methodical procedures (or algorithms) that is the basis of the acquisition, representation, processing, storage, communication of, and access to, information. The most important aspect of a Masters (MS) in Computer Science is problem-solving. Students study the design, development and analysis of software and hardware used to solve problems in a variety of business, scientific and social contexts.

Course Structure

Data Science students deal mainly with the data and spend a lot of time in the process of collecting, cleaning, and wrangling data. Few of the courses are listed below :

  • Advanced Programming Techniques
  • Data Acquisition / Management
  • Computational Math
  • Visual Analytics
  • Statistics and Probability
  • Mathematical Modeling Techniques
  • Simulation and Modeling Techniques
  • Business Analytics and Data Mining
  • Machine Learning and Big Data
  • Web Analytics
  • R Programming

Course Subjects

Computer Science students are required to contribute meaningfully on the field in either industry or research jobs. In either they must learn modern computing skills. Various subjects deal specifically with individual topics Some of the courses covered in a MS in Computer Science include:

  • Discrete Mathematics for Computer Science
  • Data Structures and Algorithms
  • Compiler Design
  • Database Management
  • Artificial Intelligence
  • Machine Learning
  • Software Engineering
  • Paradigms of Programming
  • Computer Networks
  • Computer Architecture

Top Specializations

MS in Computer Science courses offer various specializations. Some of these are listed below:

  • Big Data, Cloud Computing
  • Computer Architecture
  • Computer Networks
  • Cyber-Physical Systems, Internet of Things
  • Cybersecurity, Privacy, and Trust
  • Embedded Systems, Real-Time Systems
  • High-Performance Computing, Parallel/Distributed Computing
  • Intelligent Systems, Machine Learning, Robotics
  • Mobile Computing, Social Networks
  • Reconfigurable Computing
  • Computational Geometry
  • Data Structures
  • Discrete Mathematics

Core Skills

Top Skills You Will Learn :

  • Fundamentals of Data Science
  • Statistics
  • Programming knowledge
  • Data Manipulation and Analysis
  • Data Visualization
  • Machine Learning
  • ]Deep Learning
  • Big Data
  • Software Engineering
  • Model Deployment
  • Communication Skills
  • Storytelling Skills
  • Structured Thinking
  • Curiosity


To be able to pursue a MS in CS program, candidates should possess the right set of skills to become successful in the future. The requirements for a Masters in Computer Science vary from university to university, some of the fundamental ones are listed below:

Most of the universities in the USA, Canada require you to give the GRE. Few universities from Germany require GRE scores. However, GRE is not required for admission to Australian universities.

IELTS or TOEFL is compulsory for acquiring student visa and as a proof of English proficiency.

Aspirants must have completed a Bachelor’s degree in the same specialization with a passing percentage in aggregate of the subjects studied at the degree level.

Top Scholarships

20 Great Scholarships for Data Science and Big Data :

1. ACM SIGHPC/Intel Computational & Data Science Fellowship
2. Acxiom Corporation Diversity Scholarship
3. Bill Caspare Memorial Diversity Scholarship
4. CA Technologies Fellowship for Women
5. Daniel Larose Scholarship for Data Mining Excellence
6. Fisher Family Fund Fellowship Program
7. GAANN PhD Fellowship in Big Data Computing Research
8. HIMSS Minnesota Graduate Health IT Scholarship
9. Ike Wai Graduate Scholarship Program
10. INFORMS Analytics Society Student Scholarship
11. Jack Larson Data for Public Good Fellowship
12. Lilly Endowment Scholarship for Data Science
13. Milliman Opportunity Scholarship Fund
14. MinneAnalytics Data Science Scholarship
15. Portland DPMA Chapter Scholarships
16. Remote DBA Experts to Students Scholarship
17. Russ Peterson Technology Scholarship
18. Strong Analytics Data Science Scholarship
19. UNCF/Alliance Data Scholarship and Internship
20. William “Bill” Inmon Scholarship for Data Analytics

Work Opportunities

After completing a Masters in Data Science degree, you can be hired for numerous jobs some of which are listed below:

  • Data Scientist
  • Data Analyst
  • Big Data Engineer
  • Business Analyst
  • Statistician


Ques. What are the subjects under Master in Data Science? 

Ans. The subjects under a master in data science include:

  • Machine learning
  • Probability and statistics
  • Data mining
  • Big data
  • Object-oriented programming
  • Data manipulation and management

Ques. What are the job roles after MS in Data Science? 

Ans. The job roles an international student can explore after MS in Data Science include: 

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Mining Engineer
  • Data Architect
  • Data Statistician
  • Project Manager

Ques. What is the duration of masters in Data Science abroad? 

Ans. The duration of a full-time MS in Data Science course is 2 years. 

Ques. Why is Masters in Data Science course popular?  

Ans. Earning a master's in data science can help you gain a broad skill set that can be applied to many tech-related careers, such as data engineering, data architecture, or computer programming.

Ques. What is the requirement of Masters in Data Science course abroad?  

Ans. A masters in data science admission requires: 

  • An undergraduate degree with strong quantitative and computational background
  • Statement of Purpose
  • Letter of Recommendation
  • English Proficiency (IELTS/TOEFL/PTE/etc.)