Biostat 203B





Course Schedule

BIOSTAT 203B tentative schedule and handouts (expect frequent updates)

Recommended readings:

Week Tuesday Thursday Homework
1 1/7 introduction, course logistics [slides: Rmd, html], Linux basics [slides: Rmd, html] 1/9 Lab 1 [slides: Rmd, html], Windows instructions (by Brendon Chau) [slides: Rmd, html]  
2 1/14 reproducible research [slides: Rmd, html], Git/GitHub [slides: Rmd, html], RStudio cheatsheet, RMarkdown cheatsheet 1/16 Lab 2 [slides: Rmd, html] HW1: Rmd, html
3 1/21 import and tidy data [slides: Rmd, html] 1/23 data visualization with ggplot2 [slides: Rmd, html]  
4 1/28 visualizing longitudinal data [slides: Rmd, html] 1/30 data transformation with dplyr [slides: Rmd, html] HW2: Rmd, html
5 2/4 date and time [slides: Rmd, html], strings and regex [slides: Rmd, html] 2/6 Lab  
6 2/11 web scraping [slides: Rmd, html], shiny for interactive document [slides: Rmd] 2/13 Lab (HW3) HW3 Rmd, html
7 2/18 Databases intro. [slides: Rmd, html], dbplyr [slides: Rmd, html] 2/20 cloud computing with GCP [slides: Rmd, html]  
8 2/25 R programming (benchmark, debug, profile) [slides: Rmd, html], Rcpp, parallel computing, R package [slides: Rmd, html] 2/27 cluster computing at UCLA [tutorial], Docker  
9 3/3 neural network and deep learning (intro.) [slides: Rmd, html] 3/5 Lab: getting started with hw4 HW4 Rmd, html
10 3/10 neural network and deep learning (examples) [slides: Rmd, html] 3/12 cancelled EMR/EHR [slides: Rmd, html]