This is an introductory course in Artificial Intelligence It teaches the basic concepts, principles, and fundamental approaches to Artificial Intelligence. Its main topics include AI Fundamentals, Probability and Statistics, Python Essentials, Supervised Machine Learning, Unsupervised Machine Learning, Neural Networks, Reinforcement Learning, Deep Learning, Natural Language Processing, Decision Tree/Search Algorithms and Intro to Assured Autonomous Systems. Prerequisites: The student should have taken an undergraduate level course on, or be otherwise familiar with, operating systems and networks. Prior programming experience with C, Python or Java is highly recommended. Knowledge of algebra and discrete mathematics is also recommended.
Course Offerings
There are no sections currently offered, however you can view a sample syllabus from a prior section of this course.