COMP338: Artificial Intelligence

Second Semester 2025/26

Hisham Ihshaish

Department of Computer Science, Birzeit University

Book your final presentation slot Please book as early as possible: this is one shared calendar booked across three courses (AI, Software Engineering and HCI), so slots fill up fast. Wednesday and Thursday are on campus (Masri 320); Friday and Saturday are online on MS Teams with your camera on. Open booking →

Quizzes & Exams

Quiz #1: Problem formulation & uninformed search

Quiz #1 (Section 3), with every question reproduced as it appeared on the paper and full worked solutions plus marking criteria: the Map Colouring problem formulation, and DFS / Uniform-Cost Search on a weighted graph.

Open quiz & answers

Part I: Problem Solving by Search

Lecture material by Prof. Mustafa Jarrar (Birzeit University). Open each lecture's slides below; the chapters marked companion are expanded into interactive, worked walkthroughs on this site. Full course: jarrar.info/courses/AI.

1 Introduction to Artificial Intelligence Slides

2 Intelligent Agents Slides

3 Uninformed Search Algorithms Slides Companion

4 Informed Heuristic Search Algorithms Slides Companion

5 Local Search Algorithms Slides Companion

6 Games and Adversarial Search Slides Lecture deck Companion

Part II: Machine Learning

Lecture slides for this block are posted here for direct access. The block follows the structure of Prof. Mustafa Jarrar's AI course; his reference slides are linked alongside each lecture where available. Full course: jarrar.info/courses/AI.

7 Introduction to Machine Learning Slides Jarrar's version

8 Accuracy & Evaluation Measures Slides

9 Decision Trees Slides Jarrar's version

10 Linear Regression Slides Jarrar's version

Part III: Natural Language Processing

Lecture material by Prof. Mustafa Jarrar (Birzeit University). Open each lecture's slides below. Full course: jarrar.info/courses/AI.

11 Introduction to Natural Language Processing Slides

12 Probabilistic Language Modeling — N-grams Slides

Study Companions

Problem Formulation and Search Algorithms

An interactive walkthrough of how AI problems are formulated as search: states, actions, goal tests, and path costs, followed by uninformed and informed search algorithms with worked examples. Covers chapters 2 to 4 of the course (problem-solving agents, uninformed search, informed search, local search) plus memory-bounded heuristic search.

Open companion

Games and Adversarial Search

An interactive walkthrough of Chapter 5: game trees, minimax, and alpha–beta pruning, with a step-through tree visualiser (minimax and alpha–beta on the same tree, with live α/β windows and pruning), a move-ordering efficiency demo, an evaluation-function calculator, and a tic-tac-toe board you can play against an unbeatable minimax opponent. Includes Jarrar's exercise tree.

Open companion