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Artificial Intelligence and Deep Learning

Survey of machine learning and intelligence



MSDS 458-DL Artificial Intelligence and Deep Learning.

An introduction to artificial intelligence, this course illustrates probability-rule-based generative models as well as discriminative models for learning from data. It reviews applications of artificial intelligence and deep learning in vision and language processing. Students learn best practices for building deep learning models for classification and regression. The learn about feature engineering, autoencoders, and strategies of unsupervised and semi-supervised learning, as well as reinforcement learning. This is a project-based course with extensive programming assignments. Prerequisites: (1) MSDS 420-DL Database Systems or CIS 417 Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435 Practical Data Science Using Machine Learning.

Students benefit by taking the Python Learning Studio and MSDS 430 Python for Data Science prior to taking this course.

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