Economic Data Analysis (R & Python)

Catalog description

In this course, you’ll learn the basics of coding for data analysis using R and Python. This is a project-based course to help you learn the practicalities of working with data, which includes how to find data sources, how to collect your own data, data cleaning, data visualization and basic data analysis. You’ll apply your knowledge of statistics and econometrics with the ultimate goal to answer a research question in economics or business. Python is a robust computer language with a powerful set of libraries that can enable you to do anything from building a software program to machine learning. We will focus on web scraping, data cleaning, and visualization in Python using pandas, numpy, beautiful soup, matplotlib, and seaborn, among others. In R, we will primarily focus on econometrics and visualization. This course is not meant to substitute statistics or econometrics, but rather complement it. As such, I will expect that you already know major concepts, and will not go over it, but rather teach applications. These programs are widely used in many scientific areas for data exploration. This course is an introduction to R and Python programming language for students without prior programming experience – but, programming is like any other language, it will require practice, patience, and application to become fluent. Credit Badge: Data Science.