CS 428 Artificial Intelligence

Catalog Description: 
History, fundamental principles, and future directions of A.I. Topics include state-space searching, knowledge representation, logic and deduction, natural language processing, neural networks, learning, vision, robotics, and cognitive science. Topics will be treated at a level of depth and detail appropriate for a first course in AI.
Prerequisite: 
Junior standing and CS 219 or permission of the instructor.
Credits: 
3
Offered: 
First semester
Required or Elective: 
Elective for the BS in Computer Science.
Level: 
Advanced
Coordinator: 
John Boon
Current Textbook: 
Artificial Intelligence: A Modern Approach 3rd Edition Russell & Norvig, Prentice Hall 2010
Topics covered: 
  • Introduction to Artificial Intelligence
  • Problem-Solving
  • Knowledge, Reasoning, and Planning
  • Uncertain Knowledge and Reasoning
  • Communicating, Perceiving, and Acting
  • Philosophical Foundations
Student Learning Outcomes: 

On completing this course, the student will be able to:

  • demonstrate mastery of knowledge representation suitable for AI processes and tools.
  • demonstrate mastery of standard AI search techniques.
  • demonstrate fundamental understanding of expert system construction and validation.
  • demonstrate fundamental understanding of neural network models
Relation of Course Outcomes to Program Outcomes: 

 

CS 428 Student Outcomes (SOs)
Course Learning Outcomes a b c d e f g h i j k
1. demonstrate mastery of knowledge representation suitable for AI processes and tools.  

 

 

 

2. demonstrate mastery of standard AI search techniques.

 

   

3. demonstrate fundamental understanding of expert system construction and validation.  

 

   

 

4. demonstrate fundamental understanding of neural network models.

 

   

 


 

Role in Assessment: 
Go to top