Mining the Social Web - Twitter

Interested in tapping into Twitter data so you can discover what's trending, what people are talking about, and what feelings are being expressed in people's tweets? This course teaches you how to use a powerful set of tools that will allow you to acquire, analyze, and summarize Twitter data.

You'll learn the meanings within Twitter's metadata, explore the data mining techniques of frequency analysis and sentiment, and gain experience using Python as a data mining tool. Learners should be familiar with Jupyter Notebooks and be able to install Python packages on their own using the command line.

• Learn how to interpret the metadata that accompanies every Tweet
• Master the ability to connect to the Twitter API using Python
• Acquire real life experience using Python for data mining
• Understand how to perform a frequency analysis of different words, users, or hashtags
• Learn to measure the emotional tone of Tweets by performing a sentiment analysis
• Gain experience downloading live Twitter datastreams and analyzing them for trends

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.