Loading...
You are here:  Home  >  Data Education  >  Big Data News, Articles, & Education  >  Big Data Articles  >  Current Article

Data Science Education at Rutgers: A Business-Oriented Approach

By   /  March 31, 2016  /  No Comments

Rutgers,_The_State_University_of_New_Jersey_logoMost students who study Data Science probably don’t want to become academics. They want to become working professionals who apply their analytical skills to solving real business problems. The professional master’s degree offered at Rutgers University, a Master of Business and Science in Analytics and Data Science, emphasizes both business studies and Data Science education in order to prepare students for careers in industry.

Deborah Silver, the Executive Director of the program says:

“We have more business courses than many other programs. If you’re doing analytics without understanding the value to the company, without understanding the business case, it’s not really effective.”

That means business courses make up a significant component of the 43 credits students need to take to earn the degree. “Everyone takes communication courses, everyone takes finance and accounting, everyone takes a substantial business curriculum, even though it’s within a science masters,” Dr. Silver says.

Data Science Education Drawing on Rutgers’ Faculty and Researchers

Of the 43 required credits, 19 are business courses covering finance and accounting, marketing, communication and leadership, science and technology management, and ethics and professionalism. Science courses make up the remaining 24 credits, covering analytics, statistics, databases, and Big Data and Cloud Computing.

The coursework provides students the skills to apply statistics, Machine Learning, data modeling, and other analytical techniques to large datasets in order to develop models that support data-driven decision making.

Courses are taught by Rutgers’ faculty as well as professional faculty with at least 10 years’ experience in industry. Some of the instructors are full researchers at the Rutgers Discovery Informatics Institute (RDI2). Students are encouraged to attend seminars and workshops at RDI2 in addition to the required coursework.

At RDI2 the focus is on large-scale data projects. The institute has expertise in Advanced Cyberinfrastructure (ACI), which includes supercomputers, networked mobile devices, and grids as well as the Cloud. Their researchers work with scientists in various application domains with projects that can take advantage of the ACI and help develop the programming methods to support execution in the ACI. The institute also works on solutions to Big Data problems in the life sciences and materials science.

RDI2 partners with various departments at Rutgers University, collaborating with colleagues in departments as diverse as the School or Arts and Sciences, Rutgers Business School, and the School of Communication and Information. The institute also offers its services to industry partners, to assist with the successful adoption of large-scale computing methods.

Programs to Fit Students’ Backgrounds

The students in the program come from a variety of backgrounds. Although programming is part of Data Science, the program allows students to develop their programming skills as part of their on-going studies. Students are required to have a math background that includes a year of calculus, but beyond that, their undergraduate studies vary. The school has accepted students with computer science degrees, statistics degrees, engineering degrees, and economic degrees. Most of the students have some work experience before entering the program.

There are about 50 students in each MBS cohort pursuing the concentration in analytics. The subject appeals to many of the 250 MBS students pursuing other concentrations, so there’s a much larger base of students taking the analytics courses.

For MBS students who study full time, the program can be completed in a year and a half to two years; the school has a full summer session. The school suggests starting the program in the summer for students who need to take basic computing and statistics coursework.

Not all students study full time, though. “Our program is optimized for both part-time students and full-time students. Classes are in the evening, online, and/or hybrid,” Dr. Silver says. The cost of the program depends on whether students are in state or from out of state and whether they study full time or part time. The cost for a full-time, in-state student is approximately $40,000.

 Career Preparation as Well as Academics

Students complete an analytics practicum as part of the program, solving a large analytics problem. When possible, students work on real-world problems, but since the program has part-time students who are already working in industry, companies are sometimes concerned about exposing data to competitors.

The students have access to Rutgers’ career services. The MBS program works with students individually as well, by providing executive coaching services.

“We put a heavy emphasis on networking and professional activity,” Dr. Silver says. “We provide networking opportunities, we bring professionals into the classroom, and we send students out to professional events. They must attend a number of professional events. We’re monitoring and encouraging that networking, what we call the professional component.  I haven’t seen any other programs that really do that.”

The Data Science education program has an ongoing series of events that focus on professional development as well as address practical but specialized topics in technical skills such as programming in R and Hadoop.

To date, the program has achieved full employment of its graduates. The program helps students understand the Data Science labor market through analyzing different data science job titles. The titles were culled from real job listings and included Data Scientist, Data Engineer, Data Analyst, Business Intelligence Analyst, Consultant (Analytics), and Big Data Software Developer. They’ve also brought industry leaders to campus to discuss how Data Science projects work at their companies. By understanding the skills associated with different titles and what the jobs really involve in the workplace, the school helps students map courses to career paths and prepare themselves appropriately for the jobs they want.

Alternative Programs to Meet Specific Needs

In addition to the master’s degree program, the university also offers a Certificate in Computational and Data-Enabled Science and Engineering. Obtaining the certificate, which is a 12-credit program, is an option for those students who have a master’s in another field. The program requires completing two core courses in computation and two courses in an area of specialization. Students are also required to attend a number of colloquia at RDI2.

There is also continuing education available for working professionals, either through the Division of Continuing Studies or one-day seminars at RDI2. The continuing education programs include boot camps in Big Data and provide hands-on experience with tools like R and Hadoop. These programs can be used as a bridge to the MBS for students who later decide to pursue the degree option.

Undergraduates interested in Data Science and Analytics can find related courses in several departments, including Computer Science, Statistics, and Management Information Systems.

 New Jersey Big Data Alliance

Rutgers is one of several universities that are members of the New Jersey Big Data Alliance. The alliance, which is a few years old, is intended to help develop synergies among their programs and boost economic development in the state. NJBDA will be developing other resources to help students at its member schools succeed in their Data Science and Analytics careers.

Photo credit: Rutgers University logo

About the author

Elissa brings a practitioner's insight to her writing about information technology. She holds a B.A. in Computer Science from Cornell University and an M.S. in Computer and Systems Engineering from Rensselaer Polytechnic Institute, where her thesis dealt with testing expert systems. Before becoming a writer, she put her technical training to use as a software developer and project manager at a defense consulting firm, a major telecommunications company, and one of the largest financial institutions in the United States.

You might also like...

Data Governance and Data Stewardship Drive Successful Glossaries and Dictionaries

Read More →