Course Description
Logical foundations, knowledge representation and reasoning, search, and selected topics such as natural language processing and reasoning under uncertainty.
Syllabus
Student Learning Outcomes, Goals, Objectives:
The goal of this course is to help students develop a foundational understanding of artificial intelligence, including logical foundations, knowledge representation and reasoning, search, and selected topics such as natural language processing and reasoning under uncertainty.
Students successfully completing this course will be able:
Demonstrate knowledge of fundamental concepts, methods, and algorithms in AI.
Design and implement basic AI algorithms and applications using a programming language.
Summarize and present peer-reviewed articles on theory and practice of current AI research.
Course Grading Information:
Activity/Performance Measure | Percentage/Points |
|---|---|
Assignments | 45% |
Exams | 45% |
Research paper presentation | 10% |
Grading Scale
Percentage | Letter Grade |
|---|---|
93-100 | A |
90-92 | A- |
87-89 | B+ |
83-86 | B |
80-82 | B- |
77-79 | C+ |
73-76 | C |
70-72 | C- |
67-69 | D+ |
63-66 | D |
60-62 | D- |
<59 | F |
Attendance/Participation:
Attendance/participation is not a graded component included in the student's final grade for this course.
Course Materials Purchased by the Students:
No course materials are required.
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.