R and Python Training
In each lecture notes, you will be directed to an online resource that covers the subject that we'll be learning. These lecture notes will then provide solutions to the previous problem set and walk you through problems, and eventually real projects that we have embarked on with John List. These lecture notes will be unguided but you can reach out to an RP if you have further questions beyond the solutions. Feel free to go at your own pace. Note that the course outline below is subject to change.
Python Part 1
Web scraping with BS4
regex
R Part 1
R Basics
Data cleaning
Aggregates, joins
Reshape, pivot, lubridate
OLS
Python Part 2
Advanced regex
BS4, part 2
Text mining, sentiment analysis
Selenium, part 1
Selenium, part 2
R Part 2
Matrices, logit, IV, 2SLS
Monte Carlo and simulations
Rerandomization and regression adjustments
Mathematical optimization
Machine learning
SQL
SQL
Python Part 3
scipy, machine learning
CUDA, neural networks
Classes, OOP
Functional programming (map, filter, etc.)
Iterators
Exception handling
Threading
numpy, numba
Cython
R Part 3
Classes, functional programming, exception handling, and threading in R
Expression, quasiquotations
Rcpp
Python Part 4
APIs