VNU-HUS MAT1206E: Introduction to Artificial Intelligence


This is the website for the course “Introduction to Artificial Intelligence (VNU-HUS MAT1206E)” I am participating in teaching at the University of Science, Vietnam National University, Hanoi in Semester 1 of the 2026-2027 academic year.

Announcements

  • 20/09/2026:
    • The list of recorded mini-project topics is now available. Group numbers follow the most recent assignment of the status: recorded label, from earliest to latest; presentation times have not yet been assigned. Continue proposal updates in your existing topic-board issue.
  • 19/09/2026:
    • Room update: starting with the theory class on September 18, 2026, theory classes are held in Room 205-T5. For exercise/lab sessions, the first session on September 7, 2026 was held in Room 509-T5; from September 14, 2026 onward, exercise/lab sessions are held in Room 508-T5.
    • The Week 3 preparation materials are now available: First-order Predicate Logic and First-order Predicate Logic: In-class Discussion. Please read Chapter 3 of the textbook before class.
  • 11/09/2026:
    • The Week 1 assignment is now available: Week 1 — Introduction: Exercise 1.1. It opens at 13:00 on September 11, 2026 and is due at 23:59 on September 20, 2026, ICT (UTC+7). This is individual work.
    • The Final Examination Mini-Project acceptance link is now published and also opens at 13:00 on September 11, 2026. Only each group’s founder accepts it; see the mini-project instructions.
    • Both Week 0 Classroom50 assignments closed at 12:00 on September 11, 2026.
    • The Chapter 1 slides have been updated: Introduction and Introduction: In-class Discussion. The material on where AI stands today has been rewritten and extended, including events from September 2026. Please download the new versions.
  • 05/09/2026:
  • 01/09/2026:
    • Website initialized.

Basic information

  • University: University of Science, Vietnam National University, Hanoi
  • Course code: MAT1206E
  • Section codes: MAT1206E 1, 2, 3
  • Class: K69A3
  • Credits: 3
  • Schedule: Semester 1, Academic year 2026-2027
    • Theory: Friday, 13:00 – 14:45 (Periods 7–8), Room 205-T5 from September 18, 2026 onward (September 4 and 11: Room 102-T4)
    • Exercise, Lab: Monday; September 7, 2026: Room 509-T5; from September 14, 2026 onward: Room 508-T5
      • MAT1206E 1: 07:00 – 08:45 (Periods 1–2)
      • MAT1206E 2: 07:00 – 08:45 (Periods 1–2)
      • MAT1206E 3: 08:50 – 10:40 (Periods 3–4)
  • Instructor:
    • Theory: Hoàng Anh Đức (University of Science, VNU Hanoi, hoanganhduc[at]hus.edu.vn (replace [at] with @), GitHub Username: hoanganhduc)
    • Exercise, Lab:
      • MAT1206E 1 and MAT1206E 3: Hoàng Anh Đức (University of Science, VNU Hanoi, hoanganhduc[at]hus.edu.vn (replace [at] with @), GitHub Username: hoanganhduc)
      • MAT1206E 2: Lê Huy Hùng (University of Science, VNU Hanoi, lehuyhung94[at]gmail.com (replace [at] with @), GitHub Username: HuyHung0)
  • Content: The course provides learners with knowledge about knowledge representation and representation of knowledge, together with reasoning techniques on knowledge. Some AI systems are introduced as expert systems. Through those systems, students experiment with AI programming languages or practice with open-source systems to design and build knowledge processing systems.
  • Google Classroom and Classroom50:
    • Students must sign in with a Google account, preferably an HUS email account, and complete the registration form to provide the information needed for enrollment in Google Classroom and Classroom50.
  • Assessment, grading:

Textbook, references

Materials from previous years

  • Semester 1, academic year 2025-2026: MAT1206E
  • Semester 2, academic year 2024-2025: MAT1206E

Lectures, exercises

Note: Part of the lecture content is based on the slides of Prof. Wolfgang Ertel used in lectures at Ravensburg-Weingarten University, Germany.

Mini-project timeline: Students work on their mini-projects throughout Weeks 0–9, starting in Week 0. During Weeks 8–9, students may use both theory and exercise/lab class time to discuss and work on their mini-projects.

Week Course activities Preparation for next week
0 Theory: Preliminaries
Exercise, Lab: Help students set up for the course
Classroom50: Week 0A — Individual Git and Classroom50 Practice; Week 0B — GitHub Collaboration Practice
Introduction; Introduction: In-class Discussion
Chapter 1 of the textbook
1 Theory: Introduction: In-class Discussion; Introduction
Exercise, Lab: Exercises in Chapter 1 of the textbook
Classroom50: Week 1 — Introduction: Exercise 1.1
Propositional Logic; Propositional Logic: In-class Discussion
Chapter 2 of the textbook
2 Theory: Propositional Logic: In-class Discussion; Propositional Logic
Exercise, Lab: Exercises in Chapter 2 of the textbook
Classroom50: Week 2 — Propositional Logic: Exercise 2.5
First-order Predicate Logic; First-order Predicate Logic: In-class Discussion
Chapter 3 of the textbook
3 Theory: Discussion; First-order Predicate Logic
Exercise, Lab: Exercises in Chapter 3 of the textbook
Sample code for Chapter 3
Limitations of Logic
Chapter 4 of the textbook
4 Theory: Discussion; Limitations of Logic
Exercise, Lab: Exercises in Chapter 4 of the textbook
Logic Programming with PROLOG
Chapter 5 of the textbook
5 Theory: Discussion; Logic Programming with PROLOG
Exercise, Lab: Exercises in Chapter 5 of the textbook
Sample code for Chapter 5
Search, Games, and Problem Solving
Chapter 6 of the textbook
Prof. Ertel’s lectures: Introduction; Uninformed Search; Heuristic Search; Games with Opponents
6 Theory: Discussion; Search, Games, and Problem Solving
Exercise, Lab: Exercises in Chapter 6 of the textbook
Reasoning with Uncertainty
Chapter 7 of the textbook
Prof. Ertel’s lectures: Computing with Probabilities; Maximum Entropy; LEXMED; Bayesian Networks
7 Theory: Discussion; Reasoning with Uncertainty
Exercise, Lab: Exercises in Chapter 7 of the textbook
 
8–9 Students may use both theory and exercise/lab class time to discuss and work on their mini-projects.  
10–14 Mini-project presentations and evaluations.  

Exams


History of announcements