Masters in Data Science: What, Where and How
Updated on Oct 24, 2018 - 10:02 a.m. IST by Shraya Singh

Masters in Data Science - With the exponential increase in the incorporation of technology into every walk of life, candidates qualified in the technical domain are highly in demand. It is this high requirement of technically equipped and knowledgeable individuals which has led to the outcropping of a variety of specializations and educational areas in the field of computer science and information technology. One such increasingly popular area of study is data science which involves the study and implementation of large scale data mining, analysis and programming in order to obtain useful insights and intelligence for various organizations and business enterprises. With the rate of data production having reached a staggering 2.5 exabytes per day, data science is integral towards making sense of this incomparably large rate of data production on a daily basis. Additionally, as data is produced and analyzed in nearly every industry ranging from business and science to health, an individual with educational qualifications in the domain of data science i.e. a masters in data science is open to a versatile array of professional opportunities and a career as a data scientist


Masters in Data Science: Who is a Data Scientist?

Being educationally qualified and accredited in the domain of data science, a data scientist is essentially an individual with the ability to analyze and mine large amounts of data and in turn produce useful information and action plans for industries and organizations at the professional level. In terms of traditional professional identifiers, a data scientist can be considered as the amalgamation of a computer programmer, a mathematician, an analyst, and a statistician. Contrary to popular belief, a masters in data science does not entail a career which is solely technical in nature. In fact, in many organizations and companies, data scientists are also encouraged to make data-driven organizational decisions and derive action plans to be implemented for the growth of the organization. Therefore, a data scientist is not simply an analytical thinker but is also an organizational leader with commendable communication and decision-making skills. 

Masters in Data Science: Eligibility 

Due to the highly analytical focus of the masters in data science programs, applicants are required to be inherently skilled in mathematics as well as computer programming. Apart from this, the candidate must have a recognized undergraduate degree and English language proficiency requirements need to be met. 

Therefore, in order to be eligible for any of the masters in data science programs offered worldwide, candidates need to meet the following criteria:

  • The candidate must have a strong background in mathematics.

  • The candidate must have a working knowledge of some fundamental computer science concepts such as algorithms, linear algebra, and data structures.

  • The candidate must possess a four-year bachelor’s degree. If the candidate has a three-year bachelor’s degree, an additional one year or two-year masters degree is required to confirm eligibility.

In many universities, engineering, science, and medicine are preferred domains for admission although candidates from other backgrounds are welcome to apply.

  • The candidate must satisfy the minimum English language proficiency requirement for admission to the concerned program and university of study. English language proficiency requirement can usually be satisfied through scores from the following examinations:

    • Test of English as a Foreign Language (TOEFL) iBT

    • International English Language Testing System (IELTS) Academic

    • Pearson Test of English (PTE) Academic

    • Certificate in Advanced English/Cambridge English: Advanced (CAE)

Some universities accept scores from all three English language proficiency exams whereas others may accept only specific scores. CAE scores are generally accepted in universities outside the US and Canada. TOEFL scores a preferred for US universities. The minimum scores required for the masters in data science programs at some of the top universities in the world are:

English Language Proficiency Scores for Masters in Data Science

University 

TOEFL iBT

IELTS Academic

CAE 

Stanford University

100

-

-

Carnegie Mellon University 

100

-

-

University of California Berkeley

90

7.0

-

Harvard University 

104

7.5

-

University of Oxford

100

7.0

185

ETH Zurich

100

7.0

Grade B

University of Toronto

93

7.0

-

The University of Melbourne

79

6.5

176

University of Washington

106

-

-



Masters in Data Science: Admission Requirements

The admission requirements are generally the same for any of the masters in data science programs. The following are required to complete the admission application for an MS in data science:

  • Statement of purpose (SOP): The statement of purpose should be a brief essay which focuses on the candidate’s personal and professional goals in association with the prospective program of study. It should also give a brief reason accounting for the candidate’s choice of program of study (MS in data science) as well as the specific university. 

  • Letters of recommendation (LOR): Each university requires two or three letters of recommendation from past academic or professional referees associated with the applicant. 

  • Official transcripts: Official transcripts from the previous undergraduate program of study are required. If the transcripts are not in English then an official translated document must also be provided. 

  • GRE test scores: All MS in data science programs require GRE general test scores for admission. There may or may not be a minimum score requirement for the specific university of application. Some universities also accept GMAT scores as an alternative.

  • Resume or Curriculum Vitae (highlighting developmental areas associated with MS in data science)



Masters in Data Science: Top Universities 

Many of the top universities in the world are also high ranking in the QS world subject rank for computer science and information systems and offer various programs for masters in data science. These programs may differ in duration and/or depth of study but tend to deal with the same area of study. The various programs offered by the top universities for MS in data science are given below. 


Top Universities for Masters in Data Science

University

Program 

QS Rank

Country

Subject

World

Stanford University 

MS in Statistics - Data Science

2

2

United States

Carnegie Mellon University 

Masters in Computational Data Science

3

46

United States

University of California Berkeley

Master of Information and Data Science

4

27

United States

Harvard University 

MS in Data Science

6

3

United States

University of Oxford

Master of Science in Social Data Science

7

5

United Kingdom

Master of Science in Statistical Science

ETH Zurich

Master in Data Science

9

7

Switzerland

University of Toronto

MSc in Applied Computing - Data Science concentration

10

28

Canada

The University of Melbourne

Master of Data Science

14

39

Australia

University of Washington

MS in Data Science

18

66

United States



Masters in Data Science: Fees and Funding

The annual tuition fees for masters in data science programs generally differ with the university as well as the country of postgraduate study. Depending upon the university, the annual tuition may or may not be calculated on a per-credit basis for MS in data science.

The approximate tuition fee for masters in data science at some of the top universities around the world are given below:


Masters in Data Science: Approximate Tuition Fee

Country

University

Approximate Tuition Fee per Year

United Kingdom

University of Oxford

£25,387

United States

University of Washington

USD $46,575

Switzerland

ETH Zurich

CHF 650 (per semester)

Canada

University of Toronto

CAD $56,000

Australia

The University of Melbourne

AUD $43,000

Various forms of scholarships and funding opportunities are available at the university level which includes university-wide competitive scholarships as well as teaching assistantship (TA) or research assistantship (RA) positions. Some universities offer TA and/or RA positions to all incoming students whereas others may not. 

Some notable university specific scholarships for prospective MS in data science students are:

Masters in Data Science: Notable Scholarships

Scholarship

University

Graduate Student Aid Fund

Stanford University 

Guru Gobind Singh Fellowship

University of California, Berkeley

Master Scholarship Program

ETH Zurich

Edwin S.H. Leong Scholarship

University of Toronto

Clarendon Fund

University of Oxford

Melbourne School of Engineering Foundation Scholarship

The University of Melbourne



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