Special Topics in Artificial Intelligence
An advanced, applied course on modern artificial intelligence. It covers advanced predictive modeling, sequential data analysis, anomaly detection, explainable AI, generative approaches, optimization, and data-efficient learning. The course combines conceptual understanding with practical applications, case analysis, and project-based work.
The course website is live. Lecture materials will be released week by week during the semester. Check the Schedule page for the current status of each week.
Course Overview
Artificial intelligence is increasingly used to support prediction, automation, interpretation, and decision-making across engineering and industrial domains. This course helps students move beyond introductory machine learning: you will learn to understand advanced AI concepts and to evaluate, apply, and communicate AI methods in real-world problem-solving contexts.
The course integrates lectures, hands-on practice, technical discussion, and a semester-long project. Each major topic is connected to practical applications and case studies.
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Semester at a Glance
| Week | Topic | |
|---|---|---|
| 1 | Course Introduction and Overview of Applied Artificial Intelligence | Lecture |
| 2 | Machine Learning Strategy and Best Practices | Lecture |
| 3 | Deep Learning for Structured and Engineering Data | Lecture |
| 4 | Practical Applications of Deep Learning | Practical |
| 5 | Time-Series Forecasting and Anomaly Detection | Lecture |
| 6 | Practical Applications of Time-Series and Anomaly Detection | Practical |
| 7 | AI Project Proposal and Planning | Project |
| 8 | Midterm Examination | Exam |
| 9 | Explainable and Trustworthy Artificial Intelligence | Lecture |
| 10 | Practical Applications of Explainable AI | Practical |
| 11 | Generative Modeling, Inverse Design, and AI-Based Optimization | Lecture |
| 12 | Active Learning and Data-Efficient Artificial Intelligence | Lecture |
| 13 | Practical Applications of Generative Modeling and Data-Efficient AI | Practical |
| 14 | Final Project Presentation and Demonstration | Project |
| 15 | Final Examination | Exam |