Advanced Topics in Data Science or return to Course Catalog Search
CSCI E-109b (24801)
|Harvard Extension School||Computer Science||Mark Glickman PhD, Senior Lecturer on Statistics, Harvard University - Pavlos Protopapas PhD, Scientific Program Director and Lecturer, Institute for Applied Computational Science, Harvard University - Christopher Tanner PhD, Lecturer on Computational Science, Harvard University|
|Term||Day and Time|
|Spring Term 2020 (show academic calendar)||See course description|
Building upon the material in CSCI E-109a, this course introduces advanced methods for data wrangling, data visualization, and statistical modeling and prediction. Topics include big data and database management, interactive visualizations, nonlinear statistical models, and deep learning. Students who have previously completed CSCI E-107 or CSCI E-109 cannot count CSCI E-109a or CSCI E-109b toward a degree or certificate.<br /> <br /> Prerequisites: A grade of B- or higher in CSCI E-109a. Students who have not completed CSCI E-109a should contact the instructors before registering.
Online.<br /> <br /> Optional sections to be arranged.<br /> <br /> The recorded lectures are from the Harvard John A. Paulson School of Engineering and Applied Sciences course Computer Science 109b. Registered students can ordinarily live stream the lectures Mondays and Wednesdays, 1:30-2:45 pm starting January 27 or they can watch them on demand. Videos are available within 24 hours of the lecture.<br /> <br /> Graduate credit $2,840.<br /> <br /> See <a href="http://www.extension.harvard.edu">http://www.extension.harvard.edu</a>
|Not eligible for cross-registration|