In the tutorial, we will be using city sensor data from Data Canvas to create our visualizations.
Please download the data from the following link before the session:
There's lots you can learn here. The more you know, the farther you'll be able to get in the session (but by no means are you expected to know the content here).
THIS TUTORIAL HAS REQUIREMENTS AND INSTRUCTIONS LISTED BELOW
Connecting data to business value depends on the capacity of CEOs, managers, and project leaders to understand and trust data insights. The most robust solution to bring trust in data is to allow decision-makers to explore relevant data and correlations through interactive visualizations that accurately represent data. This tutorial teaches participants the theory and know-how to design and build interactive data visualizations.
TUTORIAL REQUIREMENTS AND INSTRUCTIONS FOR ATTENDEES
Jonathan Dinu is the Co-founder and CTO of Zipfian Academy, an advanced training program for data scientists and data engineers in San Francisco. His background is in Computer Science and Physics at University of California – Berkeley. Previously, Jonathan built distributed machine learning algorithms for predictive analytics on Hadoop at Alpine Data Labs. Jonathan is a passionate teacher and speaker. He has run data science tutorials at DataWeek and PyData, and built a Data Visualization course at Udacity. Jonathan has also been a mentor at Dev Bootcamp, taught at General Assembly, and was an instructor at Hack Reactor. At Zipfian Academy, he teaches humans, who are more fun to teach than machines.
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