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)
Statistics for Data Science
Monte Carlo Methods & Markov Chain
Logical Agents
Puzzles
Knowledge Graphs
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 15 - 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)
xxxxxxx; xxxxxxxx
- Office Hours on ZOOM
xxxxxxxx
ZOOM LINK:
https://charlotte-edu.zoom.us/j/xxxxx

GTA 2
Vinya Kestur Tumakuru Arun Kumar (e-mail: vtumaku1@charlotte.edu)
- Office Hours in the KDD Lab (Woodward 402)
xxxxxxx; xxxxxxxx
- Office Hours on ZOOM
xxxxxxxx
ZOOM LINK:
https://charlotte-edu.zoom.us/j/xxxxx

GTA 3
Sathvika Patwari (e-mail: spatwar2@charlotte.edu)
- Office Hours in the KDD Lab (Woodward 402)
xxxxxxx; xxxxxxxx
- Office Hours on ZOOM
xxxxxxxx
ZOOM LINK:
https://charlotte-edu.zoom.us/j/xxxxx

Zbigniew Ras
- Office Hours in the Center City, Room 713 (Jan 21, 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/xxxxxx



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
Chapter 1
Chapter 2
Chapter 3
Chapter 4
PowerPoint
PowerPoint
PowerPoint
PowerPoint
Week 2 Jan 21 Dijkstra Algorithm
Informed Searches
Chapter 4
Games
Sudoku
PowerPoint
PowerPoint
PowerPoint
Week 3 Jan 28 Advesarial Search, Chapter 6
Sample Problems
Logical Agents, Chapter 7

Asynchronous
PowerPoint
PDF
PDF
Week 4 Febr 4 Puzzles, Exercises
Rough Sets and DS Theory
Propositional Logic
Chapter 7 PDF
PPT
PowerPoint
Week 5 Febr 11 Statistics for Data Science
Monte Carlo Simulation
Markov Chains
Knowledge Graphs
Asynchronous Video
Video
Video1, Video2
Video
Week 6 Febr 18 Exercises Project PDF
Week 7 Febr 25 Propositional Logic
First-Order Logic
Chapter 7 PowerPoint
PDF
Week 8 March 11 Review
Solutions
Asynchronous PDF
PDF
PDF
Week 9 March 18 Midterm Exam PDF
Week 10 March 25 First-Order Logic
Chapter 8
Chapter 9
Exercises, Solutions

PowerPoint
PowerPoint
PDF, PDF
Week 11 April 1 First Order Logic
Triangular norms
ML & Deep Learning
Asynchronous PowerPoint
PDF
Video
Week 12 April 8 Resolution Strategies
Fuzzy Logic
Classification Trees(CT)
Classification Rules (RSES)
CT Example
Lectures Word
PPT
PowerPoint
PowerPoint
RTF
Week 13 April 15 Large Language Models
Data Lakes, Data Lakehouse
Recommender Systems (RS)
Content-Based RS
Asynchronous Video
Video
PowerPoint
PowerPoint
Week 14 April 22 Knowledge Based RS
RS in Healthcare
RS in Business
Generative AI
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