| Week | Part 1: Data Preprocessing and Preparation and Pattern Discovery |
|---|---|
| 1 | Course Orientation; Data, Measurements, and Basic Statics of Data; Similarity Measures; Data Quality and Data Preprocessing |
| 2 | Dimensionality Reduction Methods; Pattern Discovery Basic Concepts; Efficient Pattern Mining Methods; Pattern Discovery Programming Assignment 1 |
| 3 | Pattern Evaluation; Mining Diverse Frequent Patterns |
| 4 | Sequential Pattern Mining; Graph Pattern Mining; Pattern Mining Applications: Software Bug Mining |
| 5 | Constraint-Based Mining; Pattern Mining Applications: Phrase Mining; Pattern Discovery Programming Assignment 2 |
| 6 | Part 1 Practice Exam; Part 1 Exam on Pattern Discovery |
| Week | Part 2: Cluster Analysis |
| 7 | Course Part 2 Cluster Analysis Overview; Cluster Analysis Introduction; Partitioning-Based Clustering Methods; Cluster Analysis Programming Assignment 1 |
| 8 | Hierarchical Clustering Methods; Density-Based and Grid-Based Clustering Methods; Cluster Analysis Programming Assignment 2 |
| 9 | Spring Break |
| 10 | Probabilistic Model-Based Clustering Methods; Clustering Validation; Cluster Analysis Programming Assignment 3 |
| 11 | Part 2 Practice Exam; Part 2 Exam on Cluster Analysis |
| Week | Part 3: Classification |
| 12 | Classification Overview; Decision Tree Induction; Bayes Classifier; Classification Programming Assignment 1 |
| 13 | Model Evaluation, Selection and Improvements; Classification with weak supervision; Classification Programming Assignment 2 |
| 14 | Linear Classifier and Support Vector Machines; Neural Networks and Deep Learning |
| 15 | Pattern-based Classification and K-Nearest Neighbors Algorithm |
| 16 | Part 3 Practice Exam; Part 3 Exam on Classification |