Students in the Master of Science in Analytics program moved into the second phase of their studies with the commencement of fall semester classes today. The curriculum consists of newly developed “modular” courses designed for and limited to MSA students. Unlike conventional degree programs on campus, the MSA semester is partitioned into three segments each of which is five weeks in duration. The modules are taught by an interdisciplinary team of nine faculty from six departments in four colleges. The fall semester includes modules on topics such as Time Series and Forecasting, Optimization, Text Analytics, Customer Analytics, Data Security and Privacy, Geographical Data Analytics, Survival Analysis and Data Mining. With fall semester also begins the Analytics Practicum, in which students are organized into teams and engage with sponsoring organizations to work on real-world problems.
Month: August 2007
MSA Students Celebrate End of Summer
The intensive summer program, which ran full-time daily over a continuous 5-week stretch, was concluded successfully with a luncheon celebration at Lake Johnson Recreation Center in Raleigh. The summer program included 21 lecturers and 9 invited guest speakers covering a range of topics that focused on understanding the practical application of industry standard software tools to problems in advanced analytics. Many thanks to the joint NC State-SAS team that labored over the past year to plan and organize the summer session.
Teams Present Results of Summer Project
The summer curriculum culminated today with a series of team presentations made by two dozen MSA students. The students were presented with a challenging analytics project developed by Dr. Henry Schaffer, Dr. Jerry Oglesby and Laura Ladrie, using masked data on 100,000 records of consumer transactions. Teams were set to the task of data cleaning and analysis to uncover consumer patterns relevant to the business. Each of the six teams succeeded in highlighting significant facets in the the unique data sets they were given to analyze.
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Faculty Attend Summit on Teaching Data Mining
Two members of the Analytics faculty — David Dickey and Simon Hsiang — attended an invitation-only week long program for educators who teach data mining, sponsored by SAS Institute. Topics included pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision tree, regression, and neural network models), and case studies from the fields of database marketing, financial services, Continue reading “Faculty Attend Summit on Teaching Data Mining”