Top Five Data Science Masters Programs

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Which top Masters Courses should you consider for a great career in data-science?

A frequently cited study by McKinsey predicts that by 2018, the United States could face a shortage of 140,000 to 190,000 "people with deep analytic skills" as well as 1.5 million "managers and analysts with the know-how to use the analysis of big data to make effective decisions."

The field is so hot right now that Roy Lowrance, the managing director of New York University's new Center for Data Science program says "Anything that gets hot like this can only cool off." Regardless of this, the current school year won't be over for another five months and 50% to 75% of its students already have firm job offers!

Speaking of jobs, here’s a challenge for a text-mining role in Singapore.

To say the least, data science involves some art because it requires creative experimentation. This balance of creative experimentation and detailed analysis is not attainable by everyone. Thus the demand-supply gap, as forecasted by multiple MNC’s, for the Data Scientist talent will never be completely filled!

However, if you are comfortable with numbers and know how to code, even at the basic level, a career in Data Science is something you must explore. Here, we list down some of the best courses you can undertake to get the certification of being a Data Scientist:

1. Harvard Data Science Course

This course, primarily, examines learning from data in order to gain useful predictions and insights. The people who take this course are expected to have prior programming experiences and a basic understanding of statistics. The main focus of this course is to teach students to deal with data (collect and prepare it), analyse the collected data and make useful predictions.

The 5 focus areas of this course are:

  • Data wrangling, cleaning, and sampling to get a suitable data set
  • Data management to be able to access big data quickly and reliably
  • Exploratory data analysis to generate hypotheses and intuition
  • Predictions based on statistical methods such as regression and classification
  • Communication of results through visualization, stories, and interpretable summaries

2. UC Berkeley: Master of Information and Data Science (MIDS)

The UC Berkeley School of Information offers the only professional Master of Information and Data Science (MIDS) delivered fully online. Through this program, you can achieve the Online Master’s Degree in Data Analytics [M. S.]. This can help you make sense of real-world phenomena and everyday activities by synthesizing and mining big data with the intention of uncovering patterns, relationships and trends.

This course introduces students to concepts of information systems and the role of information systems within an organization. Topics covered will include:

  • Organizational structure and behaviour
  • Types of information systems, hardware and software issues
  • Data collection tools and techniques, issues of complexity, and the relevance of information systems to larger social issues like sustainability

3. Stanford University: Master of Science in Statistics: Data Science

This program is a collaboration between Stanford’s Department of Statistics and Institute for Computational and Mathematical Engineering. The core curriculum is, as you might imagine, heavy on mathematics and computer programming. This Data Science course is carved to attract, both, engineering or science students as well as mathematically oriented students. These students are interested in better understanding of the mathematical and statistical underpinnings of data science. They are looking to gain expertise in data science and its applications.

4. Carnegie Mellon University: Master of Information Systems Management

With the MISM program, the students will be trained in business process analysis and optimization, and will be educated on data warehousing, data mining, predictive modelling, GIS mapping, analytical reporting, segmentation analysis, and data visualization. This program has an important component of experiential learning. The students are trained to acquire the skills for analytic technology practices with applied business methods.

Carnegie Mellon’s MISM focuses on three core areas:

  • Business intelligence
  • Data analytics
  • Information technology 

5. North Carolina State University: Master of Science in Analytics (MSA)

The Harvard Business Review recently identified this Institute among the best. It was identified as one of only a few sources of talent with proven strengths in data science alongside Stanford, Berkeley, Harvard, and Carnegie Mellon. The curriculum is a carefully calibrated and a mix of applied mathematics, statistics, computer science, and business disciplines.

The point to remember is that it always makes sense to get certified by trusted institutes and platforms when it comes to a niche job profile.

Which course are you taking, Mr. Data Scientist?

Author Bio:

Sudhanshu Ahuja is the founder and CEO of a Ideatory – a platform to provide companies access to top data-scientists. Ideatory counts some of the largest companies in the world as it clients.

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Tags: big, commentary, courses, data, masters, ms, science


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Comment by Gianmarco Ciarfaglia on May 26, 2016 at 11:46pm


I graduated(master's degree) 1 and half year ago in management engineering with a deep focus on operation research and machine learning. I've been working for this year as a data analyst and i decided to take a master in data science to begin my career as a data science. 

I'm now looking for an update Data science Master's ranking to take the best choice not wasting my time/money. 

Do you have any advice about where can i find a trustable and update ranking?

Is it possible to update the ranking in the article?

thank you in advance,


Comment by shubhendra vyas on March 24, 2016 at 8:14pm

Any long distance courses offered by university ?

Comment by Ebuta Osowo on June 9, 2015 at 9:50pm

University of Westminster, London - Masters of Business Intelligence and Analytics

Courses received includes:

Data Mining Principles and Applications (Machine Learning) - SAS

Data Visualisation and Dashboarding (R, SPSS, Tableau)

Web and Social Media Analytics (Text Mining) - (Python, R, Excel)

Statistics and Operational Research

Databases, Data Warehousing , OLAP 

And many more interesting modules.

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