| Week |
Course Content |
| Week 1 |
課程介紹 |
| Week 2 |
The objective and architecture of Data Governance |
| Week 3 |
Data inventory, Data modeling, and design |
| Week 4 |
Data policies: Data storage and operations, Data warehousing |
| Week 5 |
Data quality management, Data quality strategy, Standard policy |
| Week 6 |
Accessibility and Open data, Reference and master data, Date security |
| Week 7 |
清明連假 |
| Week 8 |
[Essential skills and prerequisite knowledge about ML and DL] |
| Week 9 |
[The objective and architecture o Explainable AI] |
| Week 10 |
[The classification of Explainable AI] |
| Week 11 |
[The method of explainable AI: LIME] |
| Week 12 |
[The method of explainable AI: SHAP] |
| Week 13 |
[The method of explainable AI: LRP] |
| Week 14 |
[Cases of Explainable AI (I) Image recognition] |
| Week 15 |
[Cases of Explainable AI (II) Gen AI] |
| Week 16 |
期末報告 |
self-directed learning |
   02.Viewing multimedia materials related to industry and academia.
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