Analytics: Discovery Informatics & Data Sciences
The Master's of Business and Science degree in Analytics prepares students for data-driven decision making. It brings together the fields of computer science, statistics, machine learning, data mining and big data. Students will obtain a variety of skills including the ability to analyze large datasets, the ability to develop modeling solutions to support decision making and a thorough understanding of how data analysis drives business decision making. The curriculum integrates science courses in analytics/data science with courses in business and management. If you are interested in a Hybrid/Online option, please visit our Analytics Hybrid/Online website.
Opportunities in analytics are plentiful in the tri-state area (New York, New Jersey, Pennsylvania). This program prepares students for careers in predictive modeling, business intelligence, analytics, data mining in data-driven industries such as marketing, finance, health care, biotechnology and others. See this 2016 blog about the different career options in Analytics and the skills needed to succeed.
A bachelor’s degree in any major with a GPA of at least 3.0 (a B average) and the GRE (see also the admission requirements for the MBS). Students must have at least 1 year of calculus (2 semesters and can be taken anywhere). Those without computing or statistics undergraduate may need to take introductory courses which can count towards the degree. Unsure if you're a good fit? Attend one of our online or in-person information sessions or set up an appointment with an advisor.
Analytics (2 courses):
- 16:137:550 Fundamental of Analytics (Fall, Spring) (This course covers the basics of machine learning & data mining.)
- 16:137:551 Advanced Analytics & Practicum (Summer)
Statistics (1 course):
- 16:960:563 Regression Analysis (requires background in Statistics - click here for prerequisites) (Fall,Spring,Summer)
Database Systems (1 course):
- 17:610:557 Database Design and Management (Fall, Spring)
Big Data Computing (1 course):
- 16:137:602 Cloud Computing & Big Data (Spring)
Please note: Basic Statistics and Computing courses can be taken as part of the MBS degree program and are needed for the analytics and regression course above:.
Basic Statistics Courses:
01:960:401 Basic Statistics for Research (Fall/Spring/Summer)
01:960:484 Basic Applied Statistics (Fall/Spring/Summer)
Basic Computing Courses:
16:137:603 Python for Data Science (Python) (Fall/Spring/Summer)
56:137:500 Essentials of Computational Science (Python) (Fall)
16:332:503 Programming Methodologies for Numerical Computing and Computational Finance (C++) (Fall/Spring/Summer)
Electives: Electives can be taken from a wide variety of subjects, including advanced statistics, advanced computing, business intelligence, bio-informatics, etc. See this blog about the different career types in Analytics & Data Science. Our program is flexible to meet your career objectives.
Data Science Workshops: Students in this program are encouraged to attend the workshops in R, SAS, Stata, Python, Hadoop, etc. that run every semester. We also encourage you to attend the Practicum Poster Session. These are open to all students in the program . Please see the event list for scheduling.
This concentration is being coordinated in conjunction with the Rutgers Discovery Institute. While most of the course are in New Brunswick, NJ, some of the courses are also available at the Rutgers Newark and Camden campuses. For the Online-Distance Learning option, please see here.
Dr. Manish Parashar
Dr. Shantenu Jha
Dr. Deborah Silver
Dr. Debashis Kushary
Dr. William Pottenger