• Lecture 1: Intro
• Lecture 2: R Intro
• Lecture 3: Data Visualization
• Lecture 4: Data Visualization (maps)
• Lecture 5: Different Types of Data
• Lecture 6: Data Visualization (by Rune Madsen)
• Lecture 7: Data Manipulation (split-apply-combine)
• Lecture 8: Data Manipulation (tidy data, regular expressions)
• Lecture 9: Data Gathering (web scraping)
• Lecture 10: Data Gathering (APIs, assignment 1 & rmarkdown)
• Lecture 11: Git, Github & R Markdown
• Lecture 12: Big Data in Economics
• Lecture 13: Statistical Learning: Overview
• Lecture 14: Statistical Learning: Supervised Learning
• Lecture 15: Text as Data (by Zoltan Fazekas)
• Lecture 16: Unsupervised Learning
• Lecture 17: Privacy and Ethics