**Instructors:**Chi-Kwong Li and GuanNan Wang**Meeting time and location:**W 2-2:50pm, Integrated Science Center 3280

**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 13 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 through Blackboard 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 25: Junping Shi (W&M) "EXTREEMS-QED program and biological interdisciplinary research in William & Mary"
- Feb 1: Leah Shaw (W&M) "Adaptive Networks"
- Feb 8: Anke Zuylen (W&M) "Degrees of Separation"
- Feb 15: Sarah Day (W&M) "Tools from Computational Topology"
- Feb 22: Kaitlin Keegan "Using Ice Core Data to Understand Past and Future Climate"
- March 1: Daniel Vasiliu (W&M) "The Challange of Dimensionality in Data Science"
- March 8: spring break
- March 15: John Delos (W&M) "Saving Babies with Big Data"
- March 22: Chi-Kwong Li (W&M) "Some Possible Research Projects and Techniques"
- March 29: Guannan Wang (W&M) "Spatially Varying Coefficient Models"
- April 5: Margaret Saha (W&M)
- April 12: Micheal Trotta
- April 19: Miranda Lv (AidData)
- April 26: Anh Ninh (W&M)

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:

- Machine learning from Stanford
- Graph Analytics for Big Data from UCSD