Top 6 Universities Offering Data Science Master's Degree Courses In the US

There is a skills crisis in Big Data and data science. This is being driven by the increasing demand for people capable of generating insights and making accurate predictions, using the ever-increasing amount of data we are now capturing, storing and analyzing.
This of course makes it a hot career choice at the moment. Businesses in all sectors are looking for recruits with these skills. Forward-thinking employers are also becoming more switched on to the idea of “training up” existing staff. So those already in a career but looking for a sideways-step onto a potentially more interesting or rewarding track might consider data science and analytics a very tempting option.
Despite the rise of the “citizen data scientist” – those who can show themselves capable of using data and statistics to drive change within organizations, without primarily being data scientists or analysts – academia still provides the most viable entry into the field.
So, in a series of posts I want to highlight some of the best educational opportunities available today. Starting with master’s degree programs, with pieces in the near future looking at undergraduate, PhD and free online courses.
Who could benefit from a data science master's degree?
A master’s degree could be a great next-step if you already have some experience in almost any profession, industry or field of research, and are interested in how analytics and advanced technology are going to change the game in coming years.
You might also be a recent graduate with a first degree in some aspect of IT, engineering or technology but without any work experience. In this situation, further study focused on the application of analytics and information is likely to make you a stand-out applicant. Some courses will also offer the chance for internships and industry placements which are great opportunities to build up experience and make contacts.
 Opportunities for study at master’s level are not limited to those with the time and funds for full-time education – increasingly, executive courses are offering the chance to fit study around ongoing careers with flexible part-time and online options. 


What are the best data science master's degrees?
Here is my pick of some of the leading, world-class MSc programs which have developed a reputation for excellence in teaching and for turning out high-calibre graduates.

Master of Computational Data Science, Carnegie Mellon University
CMU’s masters course is industry focused and tech giants such as Google and Amazon come to the campus to sign up students for placements and internships. So as you would expect, competition for enrolment is fierce, with an acceptance rate of 10%. A strong background in computer science, whether through prior education or work experience, is expected.
Areas of study include advanced technology-driven applications of statistics and data science such as machine learning and data mining. If you can make the cut then your prospects are great – average starting salaries for graduates are over $100,000 and most graduates receive two or more job offers.

Master of Information and Data Science, University of California, Berkeley
Many schools are now meeting the needs of students and employers by offering distance learning online. UC Berkeley’s master’s program offers a fully online course, with the only required time on Berkeley campus being the 3-4 day immersion.
Students generally compete the program in 20 months by studying two courses per semester but this can be accelerated to 12 months by taking three courses per semester. Courses include statistics for data science, applied machine learning and data visualization. Applicants are expected to have a working knowledge of the Python programming language before beginning the course.

Master of Business Analytics, MIT Sloan
The only program on this list billed as business analytics rather than data science, MITs graduate analytics option is however focused on applying data science tools to business problems. Students receive a grounding in the R statistical programming language as well as Big Data analytical tools and methodologies. Delivered only as a full-time program, this degree is tailored for career-changers – particularly in engineering, IT and scientific fields – as well as those newly graduated with degrees in maths, computer science and statistics.

Master of Science and Analytics, Northwestern University
NWU offers a choice of online or offline programs for those looking for an industry-focused masters degree in data science. As well as studying for 15 months full-time, on-campus, there’s the option of the Online Master of Science in Predictive Analytics.
Whichever option you choose, you will study data mining, predictive analytics and advanced statistics. Full-time students get the benefit of a three-month summer internship and well an 8-month industry practicum. Former students have gone on to take up job offers from global businesses including Apple, IBM, NASA, Nike and Teradata.

Master of Science in Data Science, New York University
NYU was the first university in the world to offer an MS degree in data science and its program still has a reputation as one of the best.
Delivered full-time over two years or part-time in up to five, a core concept is that students work closely with those in other fields to apply data science to solving practical, real-world problems. As well as the straightforward data science tracks, students can elect to follow other formalized tracks and focus their study on fields such as Big Data science, natural language, data and mathematics and data and physics, preparing themselves for whichever industries they are eventually targeting for employment.

Master of Science in Statistics: Data Science at Stanford University
During their time on this full-time only course, students will develop a broad understanding of, and experience working with, cornerstones of data science including statistical modelling, programming and data mining. They then go on to specialize in more in-depth fields such as data in medicine, machine learning, business intelligence and distributed data management.
 Via Fobes