Syllabus Canvas Project
Schedule
Week | Topics |
---|---|
1 | Course introduction, Introduction to Python |
2 | Introduction to data analysis in Python |
3 | Introduction to data analysis and visualization in Python |
4 | Simple linear regression, parameter estimation |
5 | Assessing the accuracy of the parameter estimates |
6 | Assessing the accuracy of the model |
7 | Confidence and prediction intervals |
8 | Multiple linear regression, categorical predictors |
9 | Model diagnostics & evaluation |
10 | Overfitting, cross-validation, more on linear regression |
11 | Logistic regression |
12 | Classifier evaluation, Introduction to design of experiments |
13 | Comparing experiments, experiments with a single factor |
14 | Randomized design, blocking factors and common designs, Latin Squares design |