Relevant Books

Data Visualization: Principles and Practice, 2nd edition Alexandru Telea

Interactive Data Visualization, 2nd edition Matthew Ward, Georges G. Grinstein, and Daniel Keim

HTML5 Graphing and Data Visualization Cookbook Ben Fhala

Prerequisite:

CMP 160 -- Computer Graphics, OpenGL or WebGL, any GUI or equivalent.

Grading Policies:

2 programming assignments (40%), 1 final project (10%), and 2 midterms (50%). There will be no final exam.

You need to pass all components in order to pass the course!

Programs are due at midnight. Programs turned in at least a full day early will earn 1% bonus credit. Late programs will not be accepted. Total bonus credits may be accumulated up to a total of 50% toward program credits. Unless noted otherwise, programs are graded roughly 70% for functionality and correctness and 30% for style, readability, documentation/writeup, and efficiency. Additional points may also be earned for extra features.

Note: This quarter, I'm experimenting with a different grade distribution for the programming aspects of this class. In the past, the 2 assigned programs were generally simpler and the focus was on the final project. This quarter, the 2 assigned programs are more demanding but also a bit open ended. The idea behind this is for most of you to expand beyond what you did for either of the 2 assigned programs for your final project. For those of you who want to do something else totally for your final project, that is still an option.

Late programs, demo, presentation, and report will not be accepted for the final project!

THERE WILL BE NO MAKE-UP EXAMS OR PROGRAMS. THERE WILL BE NO INCOMPLETES GIVEN IN THE CLASS.

Attendance: It is your responsibility to know what is covered in class. Attendance/participation/effort is crucial in determining borderline cases at the end of the quarter. Bookmark and check the class website on a regular basis for announcements.

General Policies: All course work including homeworks, programs and exams are intended as individual effort and are graded as such. It is okay to discuss general approaches and algorithms with other students, but this should be done without writing, looking, or sharing code. Cheating or plagiarism in any form will not be tolerated. Punishment will match severity of offense. You are responsible for protecting your homework solutions and programs from being copied by others. Refer to UCSC Academic Misconduct Policy for Undergraduates://www.ue.ucsc.edu/academic_misconduct.

Last modified Sunday, 02-Jun-2019 10:38:12 PDT.