Math 410-02: Data Science: Theory Applications (Spring 2016)
- Instructors: Gexin Yu, Anh Ninh and Guangnan Wang
- Meeting time and location: W 2-2:50pm, Jones Hall 131
- Purpose and Goals: The purpose of this one credit Math 410 course is to introduce students to big data analysis, data science and possible undergraduate research projects in these topics at William and Mary. The format will consist mainly of weekly talks by faculty followed by class discussions and/or exercises related to the presented topics. The typical student in this course will be in his or her sophomore or junior year and will have an interest in pursuing a research project related to computational mathematics. For many, this course can serve as a gateway to establishing a research project through the EXTREEMS-QED program.
- Course Grade: The course grade will be based on attendance and participation. Students may miss 1 of the 14 talks without penalty. Students may earn extra credit for attending EXTREEMS-QED/Math Department colloquia and other appropriate talks listed below. Attendance of classes and colloquium talks will be recorded by the organizers, and after each lecture, write (type) a summary of the talk and turn it in before next lecture. More specifically, with total of 100 points, the attendance of each talk is 4 points, participation (which includes asking/answering questions in class), and homework (which includes presentation summaries and assignments given by the speaker) account for 4 points. Attendance of each eligible Math colloquium is 2 extra points.
-
- Jan 20: Introduction and Junping Shi (W&M) slides
- Jan 27: Chi-Kwong Li (W&M, math): Matrix problems in quantum information science
- Feb 3: John Delos (W&M, physics): Electronic Detection and Diagnosis of Health and Illness of Premature Infants
- Feb 10: Sarah Day (W&M, math): Tools from Computational Topology--with applications in the life sciences
- Feb 17: Daniel Vasiliu (W&M, math): Classification of Diabetic Retinopathy Using Feature Extraction and Statistical Learning
- Feb 24: Anh Ninh (W&M, math): Challenges in SCM clinical trials
- March 2: Darren Narayan (RIT): Graph theory methods for analyzing social and neural network data
- March 9: spring break
- March 16: David Nguyen (W&M, CS): reducing Smartphone Application Delay through Read/Write Isolation
- March 23: Whitney K. Huang (Purdue): What can we learn from millennial-scale climate simulations about temperature extremes?
- March 30: Margaret Saha (W&M, biology): analysis of calcium data
- April 6: a group from Deloitte
- April 13: Ariel BenYishay (W&M, Econ, Chief Economist of AidData): Geospatial Impact Evaluation
- April 20: GuanNan Wang (W&M, Math): Bivariate Penalized Splines for Geo-Spatial Models
- April 22: Jaime Settle (W&M, government)
- April 27: Graham Taylor (University of Guelph, Canada): deep learning
There are a few interesting talks related to data analysis (update when more are available):
Also, there are two open online courses that may be interesting to some of you: