Imagine yourself as a criminal investigator. You've been tasked with searching through thousands of subpoenaed email messages for the purpose of finding evidence of fraud. What tools could you use to do your job? In this course, based on content from Matthew Russell's book, "Mining the Social Web" (O'Reilly Media), you'll learn how to forensically examine large email data sets. Designed for learners with basic Python experience, the course explains the structure of email messages, deciphers the meanings in email metadata, and shows you how to use pandas — Python's data analysis library – to organize, manipulate, and query email data. Bonus: You get to practice your detective skills on an email data set used in a real U.S. criminal investigation (i.e., the 2001 Enron fraud case).

Gain experience using a data mining toolset to forensically analyze email messages
Understand email metadata and the structure of email messages
Discover how to visualize email patterns such as who sent or received the most email
Pick up the ability to quickly search for key terms in large volumes of email messages
Learn how to use a pandas DataFrame to perform queries and manipulate 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.

Table of Contents
Mining Mailboxes
Welcome To The Course 00:02:24
About The Author 00:00:52
Why Mine Mailboxes? 00:01:23
Understanding Email 00:02:25
Downloading The Enron Data 00:02:35
Storing Mailbox Data As A DataFrame 00:08:13
Querying Your Data 00:03:51
Conclusion 00:01:54