16.712 (203): Computational Data Modeling
 
 
 
 
Course OBJECTIVES
Discussion Forumhttp://wiggio.com/group_open_join.php?groupid=1875009&password=cdmfall2013&ref=629106
SYLLABUS http://morse.uml.edu/Activities.d/CDM/docs/cdmsyllabusfall13.pdfshapeimage_4_link_0
Funding Availability for Graduate Students (US Citizens and Permanent Residents) : NSF GK-12 Vibes and Waves in Action Fellowships
For more information contact: Prof. Chandra
Email: kavitha_chandra@uml.edu 
mailto:kavitha_chandra@uml.edushapeimage_5_link_0

16.712 (203): Special Topics: Computational Data Modeling is a new interdisciplinary graduate course offered to students from the Colleges of Engineering, Science and Business. The course objectives are to provide the student analytical and computational skills for deciphering information in large data sets with application towards developing discipline specific prediction, forecasting and decision models. Statistical methods that serve as a foundation for exploratory data analysis, characterization, hypotheses and inference will be presented using an interactive R-programming platform. A particular focus of the course is on learning algorithms and machinery that can process big data sets efficiently with respect to time and computing resources. To this end, students will learn to map problems to graphical processor unit (GPU) platforms for parallel processing and apply message-passing interface (MPI) for computation on a high-performance computing cluster (HPCC). Case studies, with data drawn from the disciplines of systems biology, communications, air-traffic and social networks, text analysis, plastics manufacturing, education and medicine will be presented by faculty undertaking research in these areas.

Instructors: Prof. Chandra
Office: Falmouth 203 (CACT)
Tel: (978) 934 3356 Instructors: Prof. Kavitha Chandra
Office: Falmouth 203 (CACT)
Tel: (978) 934 3356