Welcome to CS 360/CS 686 Data Visualization! This course will introduce students to the field of data visualization.
Students will learn basic visualization design and evaluation
principles, and learn how to acquire, parse, and analyze large datasets.
Students will also learn techniques for visualizing multivariate,
temporal, text-based, geospatial, hierarchical, and network/graph-based
data. Students will utilize Processing, D3, R and ggplot2, and many other tools and languages to prototype many of these techniques on
Remember, final project presentations are Wednesday May 15 from 12:30pm to 3:30pm in the Kudlick classroom. Arrive **ON TIME** and ready to present!
Go to http://goo.gl/Sk6JT for the course evaluation survey. This is an optional, anonymous survey to provide feedback on the course. Your username will not be collected. Participating in this survey will greatly help in improving my teaching effectiveness in the future!
Some general comments regarding the prototypes:
- Late submissions did not get assigned as many reviews, since Canvas already assigned most students peer reviews at that point. I guess this is the cost of not submitting on time!
- Canvas also confused me and another student momentarily, switching or replacing our reviews. I tried to catch all cases where this happened and made a note in the comments.
- Some students did not submit everything required, submitted late, or submitted the wrong link. I will NOT be lenient in this regard on the final projects, and will dock heavily for any issues regarding the submission.
- This is a final PROJECT, not an additional homework. I expect to see a lot of work go into these projects!
TA office hours for today have been delayed to 5:00pm – 6:00pm.
The CS Tutoring Center is now accepting applications for Outstanding Student-Teachers in Computer Science for Fall 2013!
Winners of the Outstanding Student-Teacher award receive:
- An official honor from the department, which looks great on your resume.
- A tutoring position in the CS Tutoring Center, which pays a higher rate than teacher assistants.
Instead of homework grading, tutors at the CS Tutoring Center interact with students and instructors from multiple courses. You can find a comprehensive list of tutor responsibilities and a link to the application form at:
The deadline to apply is 11:59pm on May 1, 2013, and winners will be announced on May 6, 2013.
The data visualization contest has been announced!
Enter your final projects for a chance to win one of three prizes. The requirements are basically the same as your final projects, except that you must add a discussion on how your visualization(s) further the core mission and values of the University of San Francisco.
Finally! Your midterm project grades and comments have been posted on Canvas.