Assignments (Each student finishes the assignment alone)
1. Data processing and visualization
2. Decision Tree
Project (A team of 2-3 students finish the project together)
3. Anomaly Detection Competition from AIOps Challenge
Syllabus:
| Week | Date | Topic, Papers, Slides and Reading List | Algorithms & Techniques |
| 1 | Feb 28 (13:30-16:55) | Course Introduction | |
| 2 | March 7 (No class) | ||
| 3 | Mar 14 (13:30-16:55) | Video streaming | Data Visualization
Correlation, Regression, Information gain, Decision trees, Regression trees |
| 4 | Mar 21 (13:30-16:55) | ||
| 5 | Mar 28 (13:30-16:55) | Anomaly detection for time series | Time series Algorithms. |
| 6 | Apr 4 (No Class) | ||
| 7 | Apr 11 (13:30-16:55) | Anomaly localization
for time series |
Association Mining |
| 8 | Apr 18 (13:30-16:55) | ||
| 9 | Apr 25 (13:30-16:55) | Dependency Discovery:
Event-Event, Event Sequence-TS (time series), TS-TS |
KNN |
| 10 | May 2nd (No class due to school holidays) |
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| 11 | May 9 (13:30-16:55) | Event Prediction & Log Anomaly Detection | Regularization |
| 12 | May 16 (13:30-16:55) | ||
| 13 | May 23 (13:30-16:55) | Resource Management | Deep Reinforcement Learning |
| 14 | May 30 (13:30-16:55) | Project Presentation |