Big Data in Economics (EC 410/510)

This is a Masters-level course taught by Grant McDermott at the University of Oregon. It is a condensed version of a related course (with some additions) that I teach at the PhD level.

Please read the syllabus first. This will detail software requirements and installation, and give you a better sense of the aims and scope of the course.

Lectures

Notes: While I have provided PDF versions of the lectures, they are best viewed in the original HTML format. Video recordings of the lecture are only available to enrolled students.

1. Introduction [.html | .pdf | .Rmd | Videos]
2. Version control with Git(Hub) [.html | .pdf | .Rmd | Videos]
3. Learning to love the shell [.html | .pdf | .Rmd | Videos]
4. Data wrangling & cleaning: 1) Tidyverse [.html | .pdf | .Rmd | Videos]
5. Data wrangling & cleaning: 2) data.table [.html | .pdf | .Rmd ]
6. Big data I/O
7. Webscraping: (1) Server-side & CSS [.html | .pdf | .Rmd | Videos]
8. Webscraping: (2) Server-side & APIs [.html | .pdf | .Rmd | Videos]
9. Functions in R: (1) Introductory concepts [.html | .pdf | .Rmd | Videos]
10. Functions in R: (2) Advanced concepts [.html | .pdf | .Rmd | Videos]
11. Parallel programming [.html | .pdf | .Rmd | Videos]
12. Docker [.html | .pdf | .Rmd]
13. Google Compute Engine (Part I) [.html | .pdf | .Rmd | Videos]
14. Google Compute Engine (Part II) [.html | .pdf | .Rmd | Videos]
15. Databases [.html | .pdf | .Rmd | Videos]
16. Spark [.html | .pdf | .Rmd | Videos]