Masters (MS) in Data Science Abroad: Fees, Top Universities & Job Scope

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.

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

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

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

• 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

• Massachusetts Institute of Technology
• Stanford University
• Texas A&M University, College Station
• University of Michigan - Ann Arbor
• University of California , Berkeley
• University of Oxford
• Princeton University
• ETH Zurich
• University of Toronto
• University of California, Los Angeles
• University of Melbourne
• Ecole Polytechnique Fédérale de Lausanne
• California Institute Of Technology
• Columbia University
• Cornell University
• University of Edinburgh
• University of Illinois at Urbana-Champaign
• Carnegie Mellon University
• Georgia Institute of Technology
• Johns Hopkins University
• Purdue University West Lafayette
• University of Texas at Austin
• University of Southern California
• New York University
• University of Maryland, College Park
• University of Washington

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.

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

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