Eighty percent or more of the time spent on data science projects is spent acquiring data, cleaning it, and preparing it for analysis. That data can come from a variety of sources, including APIs or individual web pages. However, not all data is created equal. Once we have automated its acquisition, much of it requires lengthy cleaning and formatting before it can be used. In this course you will learn how to obtain, clean, and mashup data in preparation for analysis.
On May 9th, 2015 I am teaching a class through District Data Labs on data acquisition and wrangling with python. Our focus will be on achieving two goals:
- Understanding more about your customers from their social profiles.
- Pulling data off the web (screen scraping) for market research and getting it into a database.
This course will teach you how to organize your data and handle incoming data streams so that you can transform them into useful information and revenue. You will learn how to combine multiple data sources into a single profile and gather information from several websites. Whether you’re analyzing your customers from social media or looking at client data, you’ll be able to apply these methods to maximize your bottom line.
The early bird rate of $250 is available until April 25th.