(AI) System Programming
Spring 2025
Schedule: Mon/Wed 4:00pm-6:00pm
Location: GIST College Building C (N6), Room 110 (Zoom Online)
Instructor: Ue-Hwan, Kim (uehwan@gist.ac.kr)
Office: GIST Central Research Facilities (C11) 407
Office Hour: Tue 4pm-5pm (by appointment)
Notice
Introduction
This course provides a comprehensive introduction to artificial intelligence systems, with a focus on modeling, analyzing, and simulating complex phenomena across different domains. By integrating computational methods and theoretical insights, the course aims to equip students with the foundational knowledge and practical skills necessary to understand and design intelligent systems.
References
- Artificial Intelligence: A Modern Approach Link
- Probabilistic Graphical Models Link
- Reinforcement Learning: An Introduction Link
- The Elements of Statistical Learning Link
- Foundations of Constraint Satisfaction Link
Schedule
| Date | Topic | Materials | Homeworks |
|---|---|---|---|
| 03-03 | No Lecture (National Holiday) | ||
| 03-05 | [Module 0] Introduction | ||
| 03-10 | [Module 1] Reflex models | ||
| 03-12 | [Module 1] Reflex models | ||
| 03-17 | [Module 1] Reflex models | ||
| 03-19 | [Module 1] Reflex models | ||
| 03-24 | [Module 2] Search | ||
| 03-26 | [Module 2] Search | ||
| 03-31 | [Module 2] Search | ||
| 04-02 | [Module 2] Search | ||
| 04-07 | [Module 3] Markov decision processes | ||
| 04-09 | [Module 3] Markov decision processes | ||
| 04-14 | [Module 3] Markov decision processes | ||
| 04-16 | [Module 3] Markov decision processes | ||
| 04-21 | [Module 9] Midterm | ||
| 04-23 | No Lecture (Midterm Period) | ||
| 04-28 | [Module 4] Games | ||
| 04-30 | [Module 4] Games | ||
| 05-05 | No Lecture (National Holiday) | ||
| 05-07 | [Module 4] Games | ||
| 05-12 | [Module 4] Games | ||
| 05-14 | [Module 5] Constraint satisfaction problems | ||
| 05-19 | [Module 5] Constraint satisfaction problems | ||
| 05-21 | [Module 5] Constraint satisfaction problems | ||
| 05-26 | [Module 5] Constraint satisfaction problems | ||
| 05-28 | [Module 6] Bayes nets | ||
| 06-02 | [Module 6] Bayes nets | ||
| 06-04 | [Module 6] Bayes nets | ||
| 06-09 | [Module 6] Bayes nets | ||
| 06-11 | [Module 6] Bayes nets | ||
| 12-16 | [Module 9] Final exam | ||
| 12-18 | No Lecture (Final Exam Period) | ||