In 2011, McKinsey Global Institute forecast an enormous shortage of Data Science and Analytics professionals by 2018. Academia responded by developing a host of Data Science education programs, primarily allowing graduates with mathematical and technical backgrounds to earn a master’s degree. Since the first programs started, they have now spread to dozens of universities, and Ph.D. level programs have also begun to develop.
Despite all of those programs, they still aren’t enough to meet the industry demand. While some companies have even offered jobs to hobbyists with Hadoop clusters in their garage, others look for non-degree training from online courses and bootcamps.
Degrees are important, but according to a number of industry professionals, they aren’t nearly as important as technical proficiency. While Data Scientists need a range of skills including technical and business knowledge, a lack of business knowledge can be overcome by partnering technical workers with business experts. As a result, both hiring managers and training programs emphasize tools and analytical methods, such as Java and Python programming, R and other Analytics platforms, along with Machine Learning and other analytical techniques. Knowledge of Hadoop and related tools are also keys to employment.
University Analytics and Data Science Degrees
Traditional university programs in Analytics and Data Science are typically offered at the graduate level, with shorter programs leading to certifications, and longer programs leading to a Master of Science degree. Many programs are affiliated with an engineering or business school, although Stanford’s M.S. in Data Science degree is granted by its statistics department, and Denison University takes a liberal arts approach to its undergraduate major in Data Analytics.
Although the curriculum varies, most provide a similar foundation in databases, managing Big Data, and statistical and other methods for analyzing the data. The programs typically require a practicum or capstone project solving a real-world Big Data problem. Often the data is provided by a corporate partner of the institution.
Most of the programs have a strong emphasis on preparing students for work and have active career placement programs. In addition to studying the technical subject matter, many programs include courses to develop business skills such as project management and communications. Some programs accommodate students who are already working by offering online and evening programs, while others require an intensive full-time course of study.
Some of the schools in the U.S. with master’s degree programs in data-related fields include Columbia University, Rutgers University, Stanford University, North Carolina State University, and Carnegie Mellon University. A handful of schools currently offer Ph.D. programs, including Kennesaw State University and Brown University, and Columbia is developing a Ph.D. program as well.
There are also several undergraduate programs in Data Science or Analytics. In addition to Denison University, Auburn University, Arizona State University, University of California – Irvine, and Smith College are among the schools offering data-related bachelors degrees.
Non-Traditional Data Science Education
For those who don’t have the time or money to spend on a traditional university degree or certificate in Data Science, there are more options than ever, including online courses, bootcamps, and nanodegrees.
edX and Coursera offer massive open online courses in many subjects, including those related to Analytics and Data Science. edX’s online courses include classes developed by universities including Columbia, University of California – Berkeley, and Harvard. Students can take individual courses or complete a series of related courses to earn a certificate. Coursera also offers specializations that lead to a certificate in Data Science and Machine Learning,
Nanodegrees are similar to certification programs but typically have a narrower focus and take significantly less time to complete. Udacity offers two online nanodegrees relevant to Analytics, a Machine Learning Engineer nanodegree and the Data Analyst nanodegree. Both programs were designed with support from major technology companies including Google and Facebook, and Udacity offers a job guarantee program to students who successfully complete the coursework. Udacity offers free courses to provide the basic level of statistical understanding required to complete the nanodegree.
While most Data Science programs require a strong math and technical background, MIT’s new Big Data and Social Analytics online certificate aims to meet the needs of students who lack that background as well as those who have it. Core activities require little programming knowledge and additional activities are offered to those with more advanced skills.
The Level bootcamp is run by Northeastern University and offers programs for students with three different levels of statistics and technical background. There are numerous other bootcamp programs not affiliated with universities, such as those at Bit Bootcamp, Data Science Dojo, NYC Data Science Academy, and General Assembly. These programs focus largely on working with the tools needed to manipulate large datasets with an introduction to analytical methods. The programs vary in terms of daily time commitment, with some requiring full-time participation and some taking a few hours per day; programs vary in length as well, with some taking a month or longer and others completing in a week.
Nearly all of the academic, online, and bootcamp programs have industry connections who helped design the program, provide data for their students’ projects, and hire their graduates. In addition, there are a variety of Data Science education programs operated by technology companies themselves.
Microsoft is starting a new online professional degree in Data Science with courses made available through edX. The company also offers the Data Science Summer School for current undergraduate students in New York City; the program is led by Microsoft researchers.
EMC offers courses both online and in instructor-led sessions, both leading to Advanced Analytics Specialist certification. IBM has founded BigDataUniversity.com, offering free training in Data Science, Analytics, Big Data, and related technologies. SAS has created the SAS Academy for Data Science with two full-time, in-person bootcamps leading to SAS certifications.
The company Data Science has created DS12, a tuition-free 12-week training program that pairs students with data scientists from Data Science and other industry firms. The program focuses on programming with Scala rather than more typical languages like Python and R.
Data Science Fellowships
Students who’ve already completed graduate training in Data Science or want to add Data Science to their skillsets in other domains can pursue several fellowship opportunities to receive additional training before beginning their careers.
The Data Incubator, funded by Cornell, offers a free eight-week fellowship to Ph.D. and master’s degree holders. The program includes bootcamp modules and seminars with practicing Data Scientists. No technical background is required; the program combines technical skills such as statistics and data visualization with the soft skills needed for networking and getting hired.
Students who want to apply Big Data to solving problems for the benefit of society can pursue a summer fellowship in Data Science for Social Good at the University of Chicago. The three-month program aims to teach fellows to apply Analytics to solving problems for governments and non-profits. Fellows work on a team project and attend lectures, seminars, and workshops. Fellows receive a stipend for their participation.
The Insight Data Science Fellowship is a seven-week program for Ph.Ds and post-docs. The program is partnered with leading Silicon Valley, New York City, and Seattle technology firms, which provide mentors and hire graduates of the program. The first half of the program focuses on learning analytical skills and applying them to solve a project; the second half consists of presenting the project to companies the fellows are interested in interviewing with. Insight also offers a similar, seven-week Data Engineering Fellowship focused on skills needed to create platforms and infrastructure for working with large datasets.