CS47100: Introduction to Artificial Intelligence (Spring 2026)

Images generated from Nano Banana with text prompt A class on Artificial Intelligence at Purdue University, digital art.


Course Information

Artificial intelligence (AI) is about building intelligent machines that can perceive and act rationally to achieve their goals. To prepare students for this endeavor, we cover the following topics in this course: Search, constraint satisfaction, logic, reasoning under uncertainty, machine learning, and planning. There will be four assignments in the form of both written and programming problems.

Pre-requisites:

Textbook:

Grading:

FAQ:

Instructors & TAs

Raymond A. Yeh

Instructor

Email: rayyeh [at] purdue.edu
Office Hour: Mon (9:00-10:00AM) (Ends Mar. 2)
Location: Zoom (See Ed.)

Brian Bullins

Instructor

Email: bbullins [at] purdue.edu
Office Hour: TBD (Starts Mar. 9)
Location: Zoom (See Ed.)

Jiaxin Du

Teaching Assistant

Email: du286 [at] purdue.edu
Office Hour: Fri 4:00 PM - 5:00 PM
Location: DSAI B055

Jimson Huang

Teaching Assistant

Email: huan2073 [at] purdue.edu
Office Hour: Fri 12:00 PM - 1:00 PM
Location: DSAI B063

Zhengyuan Li

Teaching Assistant

Email: li5280 [at] purdue.edu
Office Hour: Thu 1:00 PM - 2:00 PM
Location: DSAI B061

Nathan Niles Reed

Teaching Assistant

Email: nnreed [at] purdue.edu
Office Hour: Fri 2:00 PM - 3:00 PM
Location: DSAI B061

Harry Tian

Teaching Assistant

Email: tian253 [at] purdue.edu
Office Hour: Thu 4:00 PM - 5:00 PM
Location: DSAI B061

Abhijeet Vyas

Teaching Assistant

Email: vyas26 [at] purdue.edu
Office Hour: Thu 3:00 PM - 4:00 PM
Location: DSAI B061

Yuwei Yang

Teaching Assistant

Email: yang2134 [at] purdue.edu
Office Hour: Wed 2:00 PM - 3:00 PM
Location: DSAI B055

Hairong Yin

Teaching Assistant

Email: yin178 [at] purdue.edu
Office Hour: Thu 12:00 PM - 1:00 PM
Location: DSAI B055

Haomeng Zhang

Teaching Assistant

Email: zhan5050 [at] purdue.edu
Office Hour: Wed 11:00 AM - 12:00 PM
Location: DSAI B061

Kevin Zhang

Teaching Assistant

Email: zhan4196 [at] purdue.edu
Office Hour: Fri 12:30 PM - 1:30 PM
Location: DSAI B063

Mutian Zhang

Teaching Assistant

Email: zhan5048 [at] purdue.edu
Office Hour: Thu 2:00 PM - 3:00 PM
Location: DSAI B055

Time & Location

  • Time (LE1): Tuesday & Thursday (1:30-2:45 PM)
  • Location (LE1): MTHW 210
  • Time (LE2): Tuesday & Thursday (4:30-5:45 PM)
  • Location (LE2): SMTH 108

Other Resource

Course Schedule

The following schedule is tentative and subject to change.

DateEventDescriptionReadings
January 13 Lecture 1 Introduction & Overview

AIMA Ch. 1
January 15 Lecture 2 AI Representation

AIMA Ch. 2
January 19 Info. Assignment 1 released

Select from the following:
January 20 Lecture 3 Search - I: Problem Formulation

AIMA Ch. 3.1-3.3
January 22 Lecture 4 Search - II: Uninformed Search

AIMA Ch. 3.4
January 27 Lecture 5 Search - III: Informed search

AIMA Ch. 3.5-3.6
January 29 Lecture 6 Local search

AIMA Ch. 4.1
February 3 Lecture 7 Adversarial search - I: Minimax

AIMA Ch. 5.1-5.2
February 5 Lecture 8 Adversarial search - II: Alpha-Beta Pruning

AIMA Ch. 5.3
February 6 Deadline Assignment 1 due (Friday February 6, 11:59PM)

Select from the following:
February 9 Info. Assignment 2 released

Select from the following:
February 10 Lecture 9 CSP - I: Problem Formulation and Inference

AIMA Ch. 6.1-6.2
February 12 Lecture 10 CSP - II: Backtracking and Local Search

AIMA Ch. 6.3-6.5
February 17 Lecture 11 Logic - I: Propositional Logic

AIMA Ch. 7.2-7.4
February 19 Lecture 12 Logic - II: Propositional Theorem Proving

AIMA Ch. 7.5-7.6
February 24 Lecture 13 Logic - III: First Order Logic Senmatics

AIMA Ch. 8.2-8.3
February 26 Lecture 14 Logic - IV: First Order Logic Inference

AIMA Ch. 9.1-9.5
March 3 Lecture 15 Midterm Review (Last Lecture of Prof. Yeh)

March 5 Lecture 16 Probability and Uncertainty

AIMA Ch. 12.2-12.6
March 6 Deadline Assignment 2 due (Friday March 6, 11:59PM)

Select from the following:
March 9 Info. Assignment 3 released

Select from the following:
March 10 Lecture 17 Bayesian Networks - I: Representation and Semantics

AIMA Ch. 13.1-13.2
March 12 Lecture 18 Bayesian Networks - II: Independence

March 17 Info. No class (Spring Break)

Select from the following:
March 19 Info. No class (Spring Break)

Select from the following:
March 23 Exam Evening midterm exam (8:00PM - 10:00PM)

Select from the following:
March 24 --- No class (Evening midterm exam)

Select from the following:
March 26 Lecture 19 Bayesian Networks - III: Inference

AIMA Ch. 13.3-13.4
March 31 Lecture 20 Markov Decision Process - I: Problem Formulation

AIMA Ch. 17.1
April 2 Lecture 21 Markov Decision Process - II: Value Iteration

AIMA Ch. 17.2.1
April 3 Deadline Assignment 3 due (Friday Apr. 3, 11:59PM)

Select from the following:
April 6 Info. Assignment 4 released

Select from the following:
April 7 Lecture 22 Markov Decision Process - III: Policy Iteration

AIMA Ch. 17.2.2
April 9 Lecture 23 Reinforcement Learning - I: Problem Formulation

AIMA Ch. 22.1-22.2
April 14 Lecture 24 Reinforcement Learning - II: Q-Learning

AIMA Ch. 22.3
April 16 Lecture 25 Supervised Learning - I: Overview

AIMA Ch. 19.1-19.2
April 21 Lecture 26 Supervised Learning - II: Model Search and Evaluation

AIMA Ch. 19.4
April 23 Lecture 27 Supervised Learning - III: Deep Learning

AIMA Ch. 21.1
April 24 Deadline Assignment 4 due (Friday April 24, 11:59PM)

Select from the following:
April 28 Lecture 28 Extra Topic: Computer Vision

AIMA Ch. 25
April 30 Lecture 29 Final Review

May 4-9 Exam Final Exam (TBD)

Select from the following:

Policies

Regrade Requests

After an assignment is graded, students have three days to request a regrade. After this period, the grade is finalized.

Late & Absence Policy

A 10% penalty will be applied (per day) to late assignments. Assignments that are more than two days late will not be accepted. For the consistency and fairness to all students, we follow the policy and absence request through the Office of the Dean of Students (ODOS). If ODOS gives the final decision to the instructor then the request will be denied.

Academic Honesty

Please refer to Purdue's Student Guide for Academic Integrity. Academic dishonesty will result in a failing grade for the course and reported. It is one's responsibility to prevent others from copying your work.

Accessibility

Purdue University strives to make learning experiences as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, please contact the Disability Resource Center at: drc@purdue.edu or by phone at 765-494-1247 and the course instructor to arrange for accommodations.

Classroom Guidance Regarding Protect Purdue

Any student who has substantial reason to believe that another person is threatening the safety of others by not complying with Protect Purdue protocols is encouraged to report the behavior to and discuss the next steps with their instructor. Students also have the option of reporting the behavior to the Office of the Student Rights and Responsibilities. See also Purdue University Bill of Student Rights and the Violent Behavior Policy under University Resources in Brightspace.

University Policies

Please refer to additional university policies in BrightSpace.