ITCS 6150/8150             Artificial Intelligence                 Spring 2025


Textbook (suggested):
Artificial Intelligence, a Modern Approach
Stuart Russell, Peter Norvig
Prentice Hall Series in AI

Course Syllabus for ITCS 6150/8150

Agents
Search Algorithms (Uniformed, Informed, Adversarial)
Logical Agents
Puzzles
Knowledge Graphs
Statistics for Data Science
Monte Carlo Methods & Markov Chain
Rough Sets and Dempster-Shafer Theory
Propositional Logic
First-Order Logic
Resolution
Triangular Norms
Fuzzy Logic
Data Lakes
Machine Learning & Deep Learning
Large Language Models
Generative AI
Folksonomy
Recommender Systems
Recommender Systems in Business, Healthcare, Art

Office Hours (January 20 - May 2)

If you have questions concerning any topic covered in the class, please join me or my TAs during our office hours scheduled either in the KDD Lab (Woodward 402), Center City 713, or on ZOOM every week. No office hours on March 3-7 (Spring Break)

Office hours in the KDD Lab or ZOOM sessions are listed below:

GTA 1
Vibha Kestur Tumakuru Arun Kumar (e-mail: vtumakur@charlotte.edu)
- Office Hours in the KDD Lab (Woodward 402)
Tuesday, 4-6:00pm; Wednesday, 12-2:00pm
- Office Hours on ZOOM
Thursday, 12:00-2:00pm
ZOOM LINK:
https://charlotte-edu.zoom.us/my/vtumakur

GTA 2
Vinya Kestur Tumakuru Arun Kumar (e-mail: vtumaku1@charlotte.edu)
- Office Hours in the KDD Lab (Woodward 402)
Monday, 4-6:00pm; Wednesday, 4:00-6:00pm
- Office Hours on ZOOM
Friday, 12:00-2:00pm
ZOOM LINK:
https://charlotte-edu.zoom.us/my/vtumaku1

GTA 3
Sathvika Patwari (e-mail: spatwar2@charlotte.edu)
- Office Hours in the KDD Lab (Woodward 402)
Wednesday, 2:00-4:00pm; Thursday, 2:00-4:00pm
- Office Hours on ZOOM
Friday, 2:00-4:00pm
ZOOM LINK:
https://charlotte-edu.zoom.us/my/spatwar2

Zbigniew Chris Ras
- Office Hours in the Center City, Room 713 (Febr 4, 18, 25, March 25, April 8, 22, 30).
Tuesday: 2:30-4:00pm
-Office Hours on ZOOM (Jan 28, Febr 11, March 11, April 1, 15, 29)
Tuesday: 12:30-2:00pm
ZOOM LINK: https://charlotte-edu.zoom.us/j/97233867593

LINK TO CLASS GOOGLE DRIVE FOLDER

What subjects and when will be covered:

Date Topic Reading Slides
Week 1 Jan 14 Introduction
Agents
Uniformed Searches
Informed Searches
Optimization		 Chapter 1
Chapter 2
Chapter 3
Chapter 4		 PowerPoint
PowerPoint
PowerPoint
PowerPoint
PowerPoint
Week 2 Jan 21 Dijkstra Algorithm
Informed Searches
Advesarial Search		 Chapter 4
Games
Sudoku
Chapter 6		 PowerPoint
PowerPoint
PowerPoint
PowerPoint
Week 3 Jan 28 Sample Problems
Logical Agents, Chapter 7
What is Knowledge Graph
Knowledge Graphs
Asynchronous
 PDF
PDF
PDF
Video
Week 4 Febr 4 Puzzles, Exercises
Rough Sets - Video
Dempster-Shafer Theory
Propositional Logic
Decomposition Rules
Gentzen-Example		 Chapter 7 PDF
PPT
PPT
PowerPoint
JPG
PDF
Week 5 Febr 11 Statistics for Data Science
Monte Carlo Simulation
Markov Chains		 Asynchronous Video
Video
Video1, Video2
Week 6 Febr 18 DS Theory Example
Propositional Logic
First-Order Logic
 Chapter 7
Chapter 9, Part 1
Formal Definition		 PowerPoint
PowerPoint
PDF
Week 7 Febr 25 First-Order Logic
Exercises		 Chapter 9, Part 2
Resolution Strategies
Project		 PowerPoint
Word
PDF
Week 8 March 11 Midterm Exam Sample
Review AI1
Review AI2		 Asynchronous PDF
PDF
PDF
Week 9 March 18 Midterm Exam PDF
Week 10 March 25 Resolution - Exercises Midterm Exam Solutions
Exercises, Solutions		 PDF
PDF, PDF
Week 11 April 1 Machine Learning
ID3, Random Forest
Deep Learning		 Asynchronous Video1
PPT, Video
Video2
Week 12 April 8 Triangular norms
Fuzzy Logic
RSES Software		 Lectures PDF
PPT
PowerPoint
Week 13 April 15 Large Language Models
Data Lakes, Data Lakehouse
Recommender Systems (RS)		 Asynchronous Video
Video
PowerPoint
Week 14 April 22 Content-Based RS
Knowledge Based RS
RS in Healthcare
RS in Business
Generative AI		 Lectures PowerPoint
PowerPoint
PowerPoint
PowerPoint
Video
Week 15 April 29 Review Asynchronous Link
April 30 PROJECT DUE DATE
Maximum 4 people on the team
Project Rubric 		Will be posted later on
Final May ?? Final Exam
Association Rules Video 1, Video 2 Link


ADDITIONAL PRESENTATIONS

  • Exercise: Mini-Max 9 pennies (PPT format)
  • NPS Project (PPT Format)
  • SAS Project (PPT Format)
  • Intelligent Agents or alternate Presentation (PPT format)
  • More about Intelligent Agents (PPT format)
  • Solving Problems by Searching or alternate Presentation (PPT format)
  • Informed Search Algorithms or alternate Presentation (PPT format)
  • Constraint Satisfaction Problems or alternate Presentation (PPT format)
  • Game Playing or alternate Presentation (PPT format)
  • Agents and Propositional Logic or alternate Presentation (PPT format)
  • Logic Agents (PPT format)
  • First Order Logic (FOL) or alternate Presentation (PPT format)
  • Inference in FOL or alternate Presentation (PPT format)
  • Learning(PPT format)
  • Knowledge Discovery (PPT format)
  • Sample Problem (Resolution)

    • Midterm (City 901): March 18 (Tuesday)
    • Project (Canvas) - deadline to submit: April 30
    • Final (City 901): May ?? (Tuesday), 11:00am-1:30pm

    Grades

    • Midterm - 30 points, Final - 40 points, Project (maximum 4 people on the team) - 30 points,
    • Grade A from 90 to 100 points, Grade B from 80 to 89 points, Grade C from 65 to 79 points.

  • Sample Problems

    Class meetings:

                Location: City 901
                Time: Tuesday, 11:30am-2:15pm


    Instructor:       Zbigniew W. Ras

    Office: Woodward 430C
    e-mail: ras@uncc.edu Office Hours on ZOOM:
    When: Tuesday: 2:30-4:00pm
    Where: https://uncc.zoom.us/j/xxxxx