Course ID:
Course Code & Number
CMPE 321
Course Title
Artificial Intelligence
Level
BS
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 5 ECTS Credits
Year of Study:
Semester:
Fall
Type of Course:
Elective
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite:
Pre-requisites: NONE
Co-requisites: NONE
Catalog Description
History. Programming languages for AI. Introduction to Lisp programming. Problem solving with computers. Search strategies, game playing. Knowledge and reasoning. Knowledge representation. First-order logic, inference. Learning, inductive and statistical learning methods, Robotics systems.
Course Objectives
The objective of this course is to introduce the fundamental concepts of artificial intelligence and to explain how to use these concepts in solving problems.
Software Usage
Course Learning Outcomes
Upon succesful completion of this course, a student will be able to
1. Develop programs in LISP
2. Understand different search strategies
3. Understand the concepts of knowledge and reasoning
4. Model problems using first order logic
5. Analyze inferences and argumentations
6. Understand how machine learning works
7. Understand the fundamentals of robotic and expert systems
Learning Activities and Teaching Methods:
Telling/Explaining
Discussion/Debate
Questioning
Reading
Problem Solving
Assessment Methods and Criteria:
Test / Exam
Quiz
Assessment Methods and Criteria Others:
Design Content
Recommended Reading
Required Reading
1. Stuart Russell, Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd Edition, Prentice H
Grading
Mid-terms - 30%
Quizzes and Homeworks - 30%
Final - 40%
Learning Activities and Teaching Methods Others:
Course Coordinator:
Student Workload:
| Workload | Hrs |
|---|
Course & Program Learning Outcome Matching: