BIOSTAT 203B tentative schedule and handouts (expect frequent updates)
BruinLearn: https://bruinlearn.ucla.edu/courses/153453
Course announcements will be sent via BruinLearn.
Zoom link: https://ucla.zoom.us/j/97364661679
Office hours will be on Zoom.
Slack channel: https://uclabiostat20-upm3051.slack.com
Invitation link: https://join.slack.com/t/uclabiostat20-upm3051/shared_invite/zt-1lbqugiva-cM~EbB3wV5~5F8lgazK3Tg
Recommended readings:
Week | Tuesday | Thursday | Homework |
---|---|---|---|
1 | 1/10 introduction and course logistics [slides: qmd, html], Linux basics [slides: qmd, html] | 1/12 Lab: [slides: qmd, html] | HW1 [qmd, html] |
2 | 1/17 reproducible research [slides: qmd, html], Git/GitHub [slides: qmd, html] | 1/19 Lab | |
3 | 1/24 data ingestion and tidying [slides: qmd, html] | 1/26 data visualization with ggplot2 [slides: qmd, html] | |
4 | 1/31 data transformation with dplyr [slides: qmd, html] | 2/2 date and time [slides: qmd, html] | HW2 [qmd, html] |
5 | 2/7 strings and regex [slides: qmd, html], web scraping [slides: qmd, html] | 2/9 Lab | |
6 | 2/14 shiny for interactive graphics [slides: qmd, html] | 2/16 databases intro. [slides: qmd, html], dbplyr [slides: qmd, html] | HW3 [qmd, html] |
7 | 2/21 statistical learning (intro.) [slides: qmd, html] | 2/23 neural network (intro.) [slides: qmd, html] | |
8 | 2/28 neural network (practice) [slides: qmd, html] | 3/2 machine learning workflow using tidymodels [slides: qmd, html] | |
9 | 3/7 cloud computing with GCP [slides: qmd, html] | 3/9 cluster computing at UCLA [tutorial] | HW4 [qmd, html] |
10 | 3/14 | 3/16 R programming (benchmark, debug, profile), Rcpp, parallel computing, R package |