Analytics: discovery informatics and data sciences is offered as a
concentration within the professional science master's program described under
Business and Science 137. The objective of the master of business and science
degree with a concentration in analytics is to prepare students for data-driven decision making, and its
applications to a broad range of domains including science, engineering, and
business. It brings together fields of data management, statistics, machine
learning, and computation. Students will obtain a variety of skills including
the ability to manage and analyze very large data sets, to develop modeling
solutions to support decision making, and develop a good understanding of how
data analysis drives decision making. This curriculum also targets those
interested in data-enabled computational science and engineering (escience).
All students in the analytics: discovery informatics and data sciences
concentration must take four core courses from the following list:
Fundamentals of Analytics and Discovery Informatics (3)
Analytics and Practicum (3)
Decision trees, including algorithms, association mining,
statistical modeling, linear models, and instance-based learning. Case studies;
Please note: Basic statistics and computing courses can be
taken as part of the M.B.S. degree program and are needed for the analytics and
regression course above.
Basic Statistics Courses:
01:960:401 Basic Statistics for Research
01:960:484 Basic Applied Statistics (Fall/Spring/Summer) (3)
Basic Computing Courses:
16:137:603 Python for Data Science (Python)
56:137:500 Essentials of Computational Science (Python)
16:332:503 Programming Methodologies for Numerical Computing and Computational Finance
Full course descriptions can be found under respective departments/graduate programs.
Electives are available at http://mbs.rutgers.edu.