Advanced Machine Learning, Data Mining, and Artificial Intelligence or return to Course Catalog Search
CSCI E-82 (15407)
|Harvard Extension School||Computer Science||Peter Vaughan Henstock PhD, Artificial Intelligence and Machine Learning Technical Lead, Pfizer, Inc.|
|Term||Day and Time|
|Fall 2019 (show academic calendar)||Th 7:20 p.m. - 9:20 p.m.|
The course is intended to combine the theory with the hands-on practice of solving modern industry problems with an emphasis on image processing and natural language processing. Topics include outlier detection, advanced clustering techniques, deep learning, dimensionality reduction methods, frequent item set mining, and recommender systems. Topics also considered include reinforcement learning, graph-based models, search optimization, and time series analysis. The course uses Python as the primary language, although later projects can include R and other languages. The course also introduces some industry standard tools to prepare students for artificial intelligence jobs. Students may not receive degree or certificate credit for both this course and CSCI E-81 or CSCI E-181, offered previously.<br /> <br /> Prerequisites: This course builds upon topics covered in CSCI E-63c and CSCI E-109a and CSCI E-109b with either CSCI E-63c or CSCI E-109a as a prerequisite. Students should be proficient in Python including Pandas and readily able to load, parse, and manipulate data. A course such as CSCI E-7 or a course on Python and machine learning would be useful.
Online (live) web conference.<br /> <br /> Optional sections to be arranged.<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|