Syllabus

Learning Objectives

• Form a community of practice to learn R

• Learn and/or sharpen data wrangling, cleaning, analysis and visualization skills

• Equip you to be able to pass technical interviews

Recommended Readings

Healy, K. (2018). Data Visualization: A Practical Introduction. Princeton University Press. Free version here.

Ismay, C., & Kim, A. Y. (2019). Statistical inference via data science: A ModernDive into R and the tidyverse. Chapman and Hall/CRC. Free version here.

Peng, R. D. (2016). R programming for data science (pp. 86-181). Victoria, BC, Canada: Leanpub. Free version here.

Wickham, H., Cetinkaya-Rundel, M. & Grolemund, G (2023). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (2e) R for Data Science (2e). O’Reilly Media, Inc. Free version here.