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Data Science Education: An Overview of Academic Programs in the USA

By   /  March 9, 2017  /  No Comments

When the 2011 McKinsey report estimated that 2018 will witness a severe shortage of about “140,000 to 190,000 data analytics experts” in the US industry, the universities began to wake up to the need for new and improved US academic programs in Data Science Education. Moreover, in a 2012 blog post titled Big Data and Data Scientists It’s an issue Of Degree(s), Forbes hinted that the emergence of Big Data in the field of Data Science suddenly created an urgent need for qualified professionals who could make use of such technology for business benefits.

In response to this urgent market demand, both enterprises and universities rushed to develop appropriate postgraduate academic courses and training programs to fill the immediate gap between demand and supply. In the past several years, USA led the global Data Science academic community in spearheading many such graduate- and postgraduate- level curricula—both with and without the support of industries.

 The Current Scenario

In Do You Need a Master’s Degree to Become a Data Scientist, KDNugget provides a compilation of responses offered by prominent industry experts and leading academicians. Although the general consensus was that good practical skills can take the place of a MS degree, many of the experts argued in favor of advanced education in Data Science. Although the debate on the relative importance of   academic degrees over practical experience continues between differing parties, leading industry experts have stressed the need for advanced academic qualifications in Data Science for professional success.

The meteoric rise of Data Science in recent years has been aptly described by Roy Lowrance, the managing director of New York University’s Data Science Center, “anything that gets hot like this can only cool off.”  The high volume of job offers made to the final year Data Science students in the USA is another indication of this rising popularity of this field. However, the global MNCs predict that given the unique need for analytics experts with demonstrated explorative talents, it will not be easy to fill the demand-supply gap in Data Science.

The article titled 23 Great Schools with Master’s Programs in Data Science includes a comprehensive list of some possible programs for an aspiring Data Scientist. DATAVERSITY® has also covered several schools in our Data Science Education monthly column. The list below covers ten such programs.

Data Science Academic Programs

  • NCSU Master of Science in Analytics (MSA): The program offered by North Carolina State University was recently ranked among the top US academic programs in Data Science by The Harvard Business Review. With its inherent faculty strength in Data Science, this university’s course curriculum combines computer science, mathematics, and statistics with actual business practices. See the DATAVERSITY article here.
  • Harvard Data Science Course: The course curriculum is targeted to existing programmers with some exposure to statistics. The primary goal of this program is to engage students in practical exercises involving data collection, cleansing, and exploration. The students get a chance to use statistical procedures for predictive analysis and visualization tools for reporting results and interpretations.
  •  Bentley University Master’s of Science in Marketing Analytics: This course, specifically designed to teach marketing analytics combine compulsory coursework on market research, statistics, and strategic marketing, while allowing students to choose from three electives in marketing and/or information technology.
  •  Carnegie Mellon University: The degrees offered in this institution are known as the Master of Information Systems Management or the Master of Science in Information Technology. The purpose of the Data Science courses in this university is to cross-train students for cross variety of data skills including predictive modeling, analytics, GIS mapping, visualization, and reporting. Students work on projects in the Heinz College’s research lab to gain practical experience. See the DATAVERSITY article here.
  •  Columbia University Master’s in Data Science: A joint initiative between nine different Departments in the university, the university’s Data Science Institute features a strong interdisciplinary approach to learning. The Master’s Degree students can select from a host of elective subjects like health analytics or cyber security, or even an entrepreneurial track. Fully conducted at night, this course encourages students to join internships. Currently, half of the enrolled students are international and nearly 80 percent are enrolled part-time. See the DATAVERSITY article here.
  •  Illinois Institute of Technology Master’s of Data Science: This degree program combines theoretical studies with rigorous practical training. For its intensive real-world, this Masters of Data Science program has produced some excellent Data Scientists in the industry.
  •  Stanford University Master of Science in Statistics & Data Science: A joint program by Stanford’s Department of Statistics and Institute for Computational and Mathematical Engineering, the course emphasizes on mathematics and programming. Designed to attract the core science or engineering students, the curriculum offers a solid introduction to the mathematical and statistical foundations of Data Science. See the DATAVERSITY article here.
  • Georgia Tech Master’s of Science in Analytics: This one-year course exposes students to advanced data analytics education. Uniquely designed to suit personalized career objectives, the program offers an interesting choice between three areas of specialization, namely, Business Analytics, Analytical Tools, and Computational Data Analytics.
  • SMU Master of Science in Data Science: This course is offered online from Southern Methodist University. Primarily designed for working professionals, the program includes an interdisciplinary curriculum to well prepare the students for real-life projects skills in Data Science.
  • UC, Berkeley Online Master of Information and Data Science (MIDS): This Master of Information and Data Science degree course if offered by the University of California, Berkeley. Targeted at existing data professionals, this degree course combines theory with practical problem-solving skills development. In this course, students are introduced to the complete “data lifecycle” of real-world projects.

Data Science Education Programs in Other US schools

Review the following lists of other programs in Data Science to get a comprehensive listing of all other USA academic programs in Data Science:

Tips for Choosing a Program in Data Science

Whether an individual returning to a USA school for Data Science education is a fresh graduate, a working professional, or an experienced Data Scientist, the person needs to consider the following questions while exploring suitable academic programs:


  1. Is the program being offered by a reputed campus?
  2. Does the program design offer career opportunities for a newbie?
  3. Is the program schedule suitable for the student or a working professional?
  4. Has the program graduated sufficient volume of students?
  5. Does the program include specific courses such as R or Python that may be useful for a working professional?
  6. Does the program include sufficient amount of practical work?

According to Information Week, Master’s Degree Programs in Big Data & Analytics are designed to help IT professionals with basic undergraduate degrees, a few years of experience in data analytics jobs, and energy to make it big in advanced Data Science roles.

About the author

Paramita Ghosh has over two and a half decades of business writing experience, much of which has been writing for technology and business domains. She has written extensively for a broad range of industries, including but not limited to data management and data technologies. Paramita has also contributed to blended learning projects. She received her M.A. degree in English Literature in 1984 from Jadavpur University in India, and embarked on her career in the United States in 1989 after completing professional coursework. Having ghostwritten and authored hundreds of articles, blog posts, white papers, case studies, marketing content, and learning modules, Paramita has included authorship of one or two books on the business of business writing as part of her post-retirement projects. She thinks her professional strength is “lifelong learning.”

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