CS 4710

Artificial Intelligence

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Course Description

Pre-Requisite(s): CS 3100 with a grade of C- or better

Introduces artificial intelligence. Covers fundamental concepts and techniques and surveys selected application areas. Core material includes state space search, logic, and resolution theorem proving. Application areas may include expert systems, natural language understanding, planning, machine learning, or machine perception. Provides exposure to AI implementation methods, emphasizing programming in Common LISP.


  • Michael Freenor

     Rating

    3.44

     Difficulty

    4.00

     GPA

    4.00

     Sections

    Last Taught

    Spring 2019

  • Yen-Ling Kuo

     Rating

    3.00

     Difficulty

    3.67

     GPA

    3.64

     Sections

    1

    Last Taught

    Spring 2026

  • Mark Floryan

     Rating

    4.38

     Difficulty

    3.43

     GPA

    3.13

     Sections

    Last Taught

    Spring 2022

  • Worthy Martin

     Rating

    1.50

     Difficulty

    3.00

     GPA

    2.99

     Sections

    Last Taught

    Spring 2014

  • Yangfeng Ji

     Rating

    1.67

     Difficulty

    3.00

     GPA

    3.67

     Sections

    Last Taught

    Spring 2025

  • Ferdinando Fioretto

     Rating

    3.00

     Difficulty

    3.00

     GPA

    3.86

     Sections

    Last Taught

    Fall 2025

  • Dimitrios Diochnos

     Rating

    3.83

     Difficulty

    2.00

     GPA

    3.63

     Sections

    Last Taught

    Fall 2017

  • Lu Feng

     Rating

    2.50

     Difficulty

    2.00

     GPA

    3.96

     Sections

    Last Taught

    Fall 2025

  • Haifeng Xu

     Rating

     Difficulty

     GPA

    3.73

     Sections

    Last Taught

    Fall 2021

  • Chen-Yu Wei

     Rating

     Difficulty

     GPA

     Sections

    Last Taught

    Fall 2024

  • Zhe Zeng

     Rating

     Difficulty

     GPA

     Sections

    1

    Last Taught

    Spring 2026