Are you interested in exploring the data generated by Facebook's over 1.28 billion daily active users? Do you have some basic experience working with Python? If so, this course is for you.
You'll explore Facebook's social graph and learn how it structures data; as well as discover how to use Python and Facebook's Graph API to connect to and query the social graph for page and user data, and pick up some experience manipulating and visualizing Facebook data using the powerful Python libraries, pandas and matplotlib. The course is taught by data scientist Mikhail Klassen and is based on content from Matthew Russell's book, "Mining the Social Web" (O'Reilly Media).
- Explore the Facebook social graph and discover how it structures data
- Learn how to query Facebook data with Python and Facebook's Graph API
- Pick up techniques for comparing the popularity of Facebook pages
- Discover how to measure audience engagement with content for brand analysis
- Learn how to manipulate and visualize Facebook data
After completing his PhD in astrophysics, Mikhail Klassen transitioned to data science and refined his expertise in data mining, data analysis, and machine learning. He's now the Chief Data Scientist for Paladin:Paradigm Knowledge Solutions in Montreal, where he combines data mining and artificial intelligence to deliver personalized training for the aerospace industry.