Course description

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.

Instructor

Associated Schools

  • Harvard Division of Continuing Education

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