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Spring 2024
Apr 28, 2024
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Information Select the desired Level or Schedule Type to find available classes for the course.

CS 47100 - Introduction To Artificial Intelligence
Credit Hours: 3.00. Students are expected to spend at least three hours per week gaining experience with artificial intelligence systems and developing software. Basic problem-solving strategies, heuristic search, problem reduction and AND/OR graphs, knowledge representation, expert systems, generating explanations, uncertainty reasoning, game playing, planning, machine learning, computer vision, and programming systems such as Lisp or Prolog.
0.000 OR 3.000 Credit hours

Syllabus Available
Levels: Undergraduate, Graduate, Professional
Schedule Types: Distance Learning, Lecture, Practice Study Observation

Offered By: College of Science
Department: Computer Science

Course Attributes:
Upper Division

May be offered at any of the following campuses:     
      West Lafayette

Learning Outcomes: 1.  Develop understandings of various applications of AI. 2.  Recognize problems where AI techniques are applicable. 3.  Implement and apply basic principles of AI in solutions that require problem-solving, inference, learning, and planning. 4.  Understand how to evaluate various AI techniques and make appropriate selections.


Restrictions:
Must be enrolled in one of the following Majors:     
      Computer Science
      Computer Science Honors
      Data Science
      Data Science

Prerequisites:
Undergraduate level CS 25100 Minimum Grade of C or Undergraduate level CS 25300 Minimum Grade of C or Undergraduate level ECE 36800 Minimum Grade of C

Short Title: Intr To Artifcl Intlgn

Course Configurations:

Configuration 1: 3.0 Credits
Schedule Type Weekly Contact Hours Instructional Credit Distribution
Lecture 3 3.0
Configuration 2: 3.0 Credits
Schedule Type Weekly Contact Hours Instructional Credit Distribution
Lecture 3 3.0
Practice Study Observation 3 0.0
Configuration 3: 3.0 Credits
Schedule Type Weekly Contact Hours Instructional Credit Distribution
Distance Learning 0 3.0

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