Practical and Marketable Skills. Introduction to programming languages (e.g., R/Python) commonly used in applications of data
science, and practical data skills: collecting, scraping, cleaning, merging, processing, and visualizing data, descriptive analysis, optimization, and supervised/unsupervised statistical learning.

Synergy, Application, and Experience. Gain experience in combining these data skills with a foundational knowledge of economics to
frame and solve economic questions using real data from finance, industry, government, health, environment, among others.

Credential Requirements:

  1. Three Courses: ECON 390, ECON 470, and ECON 573 or ECON 575.
  2. Seminars: attendance at seminars of invited speakers from industry (e.g. Airbnb, Zillow, WestJet) to learn about the practice of economics and data science and to provide opportunities for career networking.