Applied computing is offered as a concentration within the professional science master's program in Camden under Business and Science 137. This
program is tailored to students that are interested in a more applied program
than the traditional master of science degree program in computer science. This concentration is
also suitable for working professionals that have some kind of scientific
training and want to improve their computational skills, but feel they do not
qualify to apply to the master of science program because their undergraduate
degree is not in computer science. The target candidate for this program is
someone with a science or engineering background, seeking professional training
in computing skills that are most applicable in industry. An undergraduate
degree in computer science is not a requirement to apply to the program.
All students in
the applied computing concentration must take four required courses and four electives. Students without a sufficient computer science background will be required to take the following courses (these do not count toward degree credit):
56:198:500 Introduction to Programming for Computational Scientists (3)
56:198:501 Introduction to Algorithms for Computational Scientists (3)
Core Courses: Required (all students):
56:198:510 Applied Algorithm Engineering (3)
Choose at least one core course from each of the following areas:
Data Management:
56:198:551 Database Systems (3)
56:198:552 Information Retrieval (3)
Security:
56:198:575 Cryptography and Computer Security (3)
56:198:548 Security in Mobile Computing (3)
Computer Networks:
56:198:546 Computer Networks (3)
56:198:549 Network Coding (3)
Electives: Choose any three or four graduate-level computer science courses to complete 24 credits. See http://cs.camden.rutgers.edu/graduate/mbs-applied-computing for course listings.
Full course descriptions can be found under the
respective graduate program entries in this catalog, or the professional science master's website: http://mbs.rutgers.edu.
Concentration Coordinator:
Professor Suneeta Ramaswami
rsuneeta@camden.rutgers.edu
