| 1 | Definition of Artificial Intelligence and Key Concepts | [1] s. 41-75; [2] s. 25; [3] s. 20-30 |
| 2 | Definition of Machine Learning and Key Concepts | [1] s. 79-109 ; [2] s.99-143; [3] s.1-13 |
| 3 | Introduction to Artificial Neural Networks | [2] s. 25-32 |
| 4 | Neural Network Architectures | [2] s.51-95 |
| 5 | Applications of AI in Pre- and Post-Disaster Phases | [2] s.25 |
| 6 | Introduction to Python Programming and Basic Concepts | [1] s. 19-38 |
| 7 | Advanced Python Topics | [1] s. 116 |
| 8 | AI Applications in Early Warning Systems for Disaster Preparedness | [1] s.60 |
| 9 | Disaster Detection and Classification Using Image Processing | [2] s.154-158; [3] s.3-36 |
| 10 | Damage Assessment with Remote Sensing Techniques After Disasters | [2] s.85 |
| 11 | Crisis Management Using Natural Language Processing (NLP) | [1] s.62 |
| 12 | AI-Powered Decision Support Systems and Disaster Response Simulations | [1] s.310-312 |
| 13 | Case Studies and Practical Applications | [1] s.204 |
| 14 | General Review and Course Wrap-Up | [1] s. 41-75; [2] s. 25; [3] s. 20-30 |