BIOSTAT M280 tentative schedule and handouts (expect frequent updates)
Readings:
| Tuesday | Thursday | Homework |
|---|---|---|
| 1/09 introduction, course logistics [slides: Rmd, html] | 1/11 Linux basics [slides: Rmd, html] | HW1: Rmd, html |
| 1/16 reproducible research [slides: Rmd, html], Git/GitHub [slides: Rmd, html] | 1/18 RMarkdown [tutorial] | |
| 1/23 data visualization with ggplot2 [slides: Rmd, html] | 1/25 cluster computing at UCLA (Dr. Raffaella D’Auria from IDRE) [slides: part 1, part 2] | |
| 1/30 data transformation with dplyr [slides: Rmd, html] | 2/01 tidy data [slides: Rmd, html] | HW2: Rmd, html |
| 2/06 stringr [slides: Rmd, html] | 2/08 shiny for interactive document [slides: Rmd, html] | |
| 2/13 Databases [slides 1: Rmd, html] | 2/15 Databases [slides 2: Rmd, html] | HW3: Rmd, html |
| 2/20 cloud computing with GCP [slides: Rmd, html] | 2/22 Docker [slides: Rmd, html] | |
| 2/27 distributed data analysis with sparklyr [slides 1: Rmd, html] | 3/01 distributed data analysis with sparklyr [slides 2: Rmd, html] | HW4: Rmd, html |
| 3/06 R programming (benchmark, debug, profile) [slides: Rmd, html] | 3/08 Rcpp, parallel computing, R package [slides: Rmd, html] | |
| 3/13 neural network and deep learning (intro.) [slides: Rmd, html] | 3/15 neural network and deep learning (examples) [slides: Rmd, html] |