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.
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.
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
Carnegie Mellon University
University of California Berkeley
University of Oxford
University of Toronto
The University of Melbourne
University of Washington
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)
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
MS in Statistics - Data Science
Masters in Computational Data Science
Master of Information and Data Science
MS in Data Science
Master of Science in Social Data Science
Master of Science in Statistical Science
Master in Data Science
MSc in Applied Computing - Data Science concentration
Master of Data Science
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
Approximate Tuition Fee per Year
CHF 650 (per semester)
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
Graduate Student Aid Fund
Guru Gobind Singh Fellowship
University of California, Berkeley
Master Scholarship Program
Edwin S.H. Leong Scholarship
Melbourne School of Engineering Foundation Scholarship
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