teaching
ML 101
Data Visualization
overview | logistics | schedule | announcements | assignments | resources
Lecture: Tue & Thu 10:10am-11:30pm (RKC 100)
Office Hours: Wednesday 1:30pm-2:30pm; Tuesday & Thursday 3pm-4pm
and by appointment (RKC 204)
Required Texts
- The Functional Art: An Introduction to Information Graphics and Visualization. Alberto Cairo. New Riders. 2012.
- Interactive Data Visualization.Scott Murray. O'Reilly. 2013. [online version]
- Visual Insights: A Practical Guide to Making Sense of Data. Katy Borner and David E. Polley. MIT Press. 2014.
- The Best American Infographics of 2014. Gareth Cook. Houghton Mifflin Harcourt. 2014.
- Now You See It: Simple Visualization Techniques for Quantitative Analysis. Stephen Few. Analytics Press. 2009.
- Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations. Isabella Meirelles. Rockport Publishers. 2013.
- Books by Tufte.
- Assignments (30%): Small weekly assignments
- Critiques (25%): Presentation and critique of course-work
- Project (25%): Individual visualization project
- Participation (20%): Positive impact on the class (and you have to be there to have a positive impact!)
- Attend class.
- Be on time.
- Participate.
- Come to class prepared. Make sure to have read the required reading BEFORE class.
- Complete all assignments and start early.
- Cooperate, but don't copy.
- Credit work, including all sources you used from the web, other books, etc.
- Sharing ideas is encouraged, but blatantly copying work without attribution will be treated as scholastic dishonesty and receive no credit.
- Keep your assignment and lab work private, a USB flash drive is recommended.