Teaching

Courses taught in 2025/26 academic year

EC349 Data Science for Economists Term 2

UG Economics, University of Warwick, slides available on request Course Page

Overview:

  1. Session 1: Introduction to R
    • Brief introduction to R, RStudio and Positron
    • Core R syntax and data types
    • Programming in R: control flow and functions.
  2. Session 2: Data wrangling and visualization, LASSO
    • Jupyter Notebooks in R
    • Installing and managing libraries: intro to tidyverse
    • Data manipulation and visualization
    • LASSO and K-fold cross-validation with cv.glmnet.
  3. Session 3: Supervised machine learning in R
    • Project-oriented setup for predictive modelling
    • Preparing data for ML models
    • Informing modelling with data insights: exploratory data analysis
    • Implementing and tuning regression trees and FNN using tidymodels.
  4. Session 4: Metalearners & AIPW
    • FNN with brulee as base learner
    • S-, T- and X-learners
    • Cross-fitted AIPW and method comparison.

EC9D8 Foundations of Data Science Term 1

MSc Economics and Data Science, University of Warwick Course Page