| Dates | Topics | Labs | Assignments/Quizzes | Exams |
| Week 1 | Introduction Data |
- | - | - |
| Week 2 | Information based learning I Information based learning II |
Lab 1 - Data preprocessing | A1 - Decision tree application | - |
| Week 3 | Information based learning III Similarity based learning I |
Lab 2 - Information based binning algorithm | - | - |
| Week 4 | Similarity based learning II Probability based learning I |
Lab 3 - data transformation and distance function | A2 - Similarity application | - |
| Week 5 | Probability based learning II Probability based learning III |
Lab 4 - Probability algorithms | - | - |
| Week 6 | Error based learning I Midterm review |
Lab 5 - Bayesian Belief Network | A3 - Probability applications | - |
| Week 7 | Midterm Error based learning II |
- | - | Midterm |
| Week 8 | Error based learning III Deep Learning |
Lab 6 - Neural network algorithm | A4 - Regression model | - |
| Week 9 | Error based learning IV Predictive Model Evaluation | Lab 7 - Model evaluation | - | - |
| Week 10 | Predictive Model Evaluation Cluster Analysis I |
Lab 8 - Model and Evaluation | A5 - Clustering application | - |
| Week 11 | Cluster Analysis II Outliers | Lab 9 - Linear Regression Model | - | - |
| Week 12 | Association I Association II |
Lab A - Association Analysis algorithm | - | - |
| Week 13 | Association III Summary/Final Review |
(Optional) Presentation | - | - |