| 1 | Introduction to Course | |
| 2 | Decision Analysis 1 | |
| 3 | Decision Analysis 2, Linear Regression | |
| 4 | Predictive Modeling, Data Collection | |
| 5 | Logistic Regression, MLE | |
| 6 | Evaluation | |
| 7 | Instance-based Models 1 - kNN | |
| 8 | Instance-based Models 2 - Trees and Rules | |
| 9 | Homework 2 - Trees and Rules | |
| 10 | Ensemble Models | |
| 11 | PCA, LDA | |
| 12 | Unsupervised Learning | |
| 13 | Neural Networks | |
| 14 | Homework 2 - Trees and Rules | Assignment due |
| 15 | Review | |
| 16 | Survival Analysis | |
| Midterm | |
| 17 | Statistical Learning Theory | |
| 18 | Model Construction Schemas 1 | |
| 19 | Model Construction Schemas 2 | |
| 20 | Preprocessing Algorithms 1 | |
| 21 | Preprocessing Algorithms 2 | |
| 22 | Analysis of Problems, Complexity | |
| 23 | Search Algorithms | |
| 24 | Bioinformatics 1 (Hypothesis Generation, Sequence Alignment) | |
| 25 | Bioinformatics 2 (Phylogenetic Trees, Haplotype Tagging) | |
| 26 | Student Project Presentation 1 | |
| 27 | Student Project Presentation 2 | |