Data Sourcing: Foundations of Data Science, Part 2.

Course Description

Data science can’t happen without data. That means the first task in any project is source – that is, to get – the raw materials that you will need. This short course discusses some of the more familiar methods of gathering data and some of the less familiar that are specific to data science. Data Sourcing is the second of seven courses designed to outline the principles and practices of applied data science.

Course Information

  • Introductory level
  • 14 streaming video tutorials
  • 53 minutes of instruction

Note. To navigate the videos, click on the menu icon (☰) in the top left of the video.

Table of Contents

1. INTRODUCTION

  1. Welcome (0:51)

2. MEASUREMENT

  1. Metrics (6:14)
  2. Accuracy (3:52)
  3. Social context of measurement (3:37)

3. GETTING DATA

  1. Existing data (7:09)
  2. APIs (6:24)
  3. Scraping (5:20)

4. MAKING DATA

  1. New data (2:16)
  2. Interviews (2:53)
  3. Surveys (3:23)
  4. Card sorting (3:38)
  5. Laboratory experiments (3:47)
  6. A/B testing (3:00)

5. CONCLUSION

  1. Next steps (0:35)