With the focus on the machine intelligence technologies around processing, representing, modeling, and learning from large quantity of data in the current web context, this course serves as a broad introduction to students of the theories, algorithms and applications of modern Artificial Intelligence (AI). Taking a data science oriented perspective, this course aims to help students to develop a broad theoretical knowledge and practical experience in AI. With the understanding that modern AI is actually a discipline of theories and techniques around the idea of data driven model-based machine intelligence, this course consists of four broad modules: 1) representation of knowledge, 2) uncertainty-based modeling and reasoning, 3) improvements with machine learning, and 4) communication with natural language processing, all of which are necessary components for an intelligent agent to engage intelligently with other agents or people in the real world. The goal of this course is to prepare students to work creatively and productively in current data-driven and intelligence-rich environment, and it is ideal for students who would like to be introduced to the techniques of modern AI. Topics include: search, logic and deduction, knowledge representation and memory organization, production systems, expert systems, planning, language understanding, and machine learning.

Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: INFSCI 2591 PROG: Sch Computing and Information
Minimum Credits: 3
Maximum Credits: 3

Current Sections

Spring 2023

Class No.DaysTimesRoomInstructor(s)TA(s)Type
25329 (1010)Th9:00 am - 11:50 amIS 405D. He