| L | Date | Lecturer | Contents | Materials |
|---|---|---|---|---|
| 1 | 22.9. | JK | Introduction, course map, requirements. Linear regression (continuous dependent variable, simple linear regression, p-values). | SAN_intro, SAN_regression, SAN_lecture_1_czech, SAN_lecture_1_english |
| 2 | 29.9. | JK | Multivariate regression (overfitting, model shrinkage). | see the previous slides, SAN_lecture_2_czech, SAN_lecture_2_english |
| 3 | 6.10. | JK | Nonlinear regression (polynomial regression, splines, local regression). | SAN_nlin_regression, SAN_lecture_3_czech, SAN_lecture_3_english |
| 4 | 13.10. | JK | Nonlinear regression (polynomial regression, splines, local regression). | see the previous slides, SAN_lecture_4 |
| 5 | 20.10. | JK | Discriminant analysis (categorical dependent variable, LDA, logistic regression). | SAN_discriminant, SAN_lecture_5 |
| 6 | 27.10. | JK | Generalized linear models (GLMs). | SAN_GLMs, SAN_lecture_7 |
| 7 | 3.11. | JK | Dimension reduction (PCA and kernel PCA). | SAN_dimred, SAN_lecture_8 |
| 8 | 10.11. | JK | Dimension reduction (other non-linear methods). | see the previous slides, SAN_lecture_9 |
| 9 | 17.11. | – | National holiday | no class |
| 10 | 24.11. | TP | Robust statistics. | lecture notes, slides, SAN_lecture_10 |
| 11 | 1.12. | TP | Anomaly detection. | SAN_anomaly, SAN_lecture_11 |
| 12 | 8.12. | ZM | Empirical studies, their design and evaluation. Power analysis. | SAN_emp_studies_power_analysis, SAN_lecture_12 |
| 13 | 15.12. | JK | Clustering (formalism, k-means, EM GMM, hierarchical). | SAN_clustering, SAN_lecture_13 |
| 14 | 5.1. | JK | Clustering (spectral clustering). | SAN_spect_clustering, SAN_lecture_14 |
| T | Date | Teacher | Contents | Materials |
|---|---|---|---|---|
| 1 | 22.9. | JB, AA, JK | Statistical testing, t-test, significance, power of the test. | san_intro.zip, r_setup.zip, pres-1.pdf |
| 2 | 29.9. | JB, AA, JK | Simple linear regression. | san_lreg.zip, R cheat sheet, pres_2.pdf |
| 3 | 6.10. | JB, AA, JK | Shrinked linear regression | san_fs.zip, assignment1.zip, pres_3.pdf |
| 4 | 13.10. | JB, AA, JK | Non-linear regression | san_nonlinear.zip, pres_4.pdf |
| 5 | 20.10. | JB, AA, JK | Discriminant analysis | san_lda.zip, assignment2.zip, reading for assignment 2, pres_5.pdf |
| 6 | 27.10. | JB, AA, JK | Generalized linear models | san_glms.zip, assignment3.zip, pres_7.pdf |
| 7 | 3.11. | JB, AA, JK | Mid-term test, the final assignment | Final Assignment |
| 8 | 10.11. | JB, AA, JK | Dimension reduction | san_dimred.zip, assignment4.zip, pres_8.pdf, assig4_R_problem.pdf |
| 9 | 17.11. | – | National holiday, dean's day | no class |
| 10 | 24.11. | TP | Robust statistics | instruction.pdf |
| 11 | 1.12. | TP | Anomaly detection – assignment | anomaly2.pdf anomaly-problems.zipNotebook in PlutoLink to Pluto |
| 12 | 8.12. | ZM | Empirical study design, power analysis | empirical_study, experiment_data_FINAL |
| 13 | 15.12. | JB, AA, JK | Clustering | san_clustering.zip, pres_13.pdf, pres_13.odp |
| 14 | 5.1. | JB, AA, JK | The final assignment – team presentations |
If you are interested and want to learn more, here are some extra resources beyond this course you can look at:
If you have a suggestion on what to add, please let us know. :)