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