Course Number:
CSCI 5450
Approved Starting Semester:
Fall 2026
Course Title:
Artificial Intelligence
Course Description (Bulletin Description):
This is a graduate-level course that covers advanced methods and applications of artificial intelligence (AI). Emphasis will be placed on the theoretical frameworks as well as on the mastery of AI programming tools. Students will review research papers and engage in a project. A significant amount of mathematics and programming background is required.
Prerequisite:
None
Co-requisite:
None
Pre/Co-requisite::
None
Dual-Listed:
None
Course Objectives (Course-level Student Learning Outcomes):
o Describe the history of AI and its foundations. o Discuss the theoretical frameworks of AI. o Examine AI applications in a variety of fields. o Investigate modern AI system development platforms. o Apply AI tools and algorithms to a specific project. o Compose a term report for the project.
Topics Covered (In Outline/Calendar):
Since this is a graduate-level course, the instructor will provide a list of topics of interest, including but not limited to theoretical methods, such as * Deep Convolutional Neural Networks * Generative Algorithms * Reinforcement Learning * Computer Vision * Monte-Carlo Tree Search * Practical applications, including ** Computer Chess ** AlphaGo from Google DeepMind ** NPCs in Video Games ** Autonomous Vehicles The instructor will also encourage students to propose their own topic for the project.
Student Learning Outcomes:
Not applicable for this course
Course Coordinator:
Dr. Jiang Li
Instructor-in-charge:
Dr. Jiang Li
Previous Professors:
Dr. Jiang Li
Technologies / Skills:
methods and applications of artificial intelligence
Textbook(s):
Fall 2026
Title:
Edition:
Author:
Publisher:
ISBN:
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