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Course Schedule: 


Date
Topic
Suppl. Reading (Chapters)
Labs Handouts
8/24
Intro     intro
8/26
Basic tasks and examples Ward: chapter 1   basic
8/31
Basic tasks and examples   lab1 see above
9/2
Data wrangling and preparation Ward: chapter 2   dataPrep
9/7
Data reduction and similarity metrics Aggarwal 2.4.3.1, 2.4.1, 6.3.1   dataRed
9/9
Dimension reduction see above   dimRed
9/14
Intro to D3 (Zoom lecture) demo code link on piazza, slides lab2 D3intro
9/16
Visual bias see links on last slide   bias
9/21
Perception and cognition Ward: chapter 3   percept
9/23
Design and aesthetics Ware:: chapter 4, Munzner: chapter 5   design
9/28
Cluster analysis Aggarwal 6.4-5   cluster
9/30

High-D data visualization: linear methods

Ward: chapter 8   highDVis
10/5
High-D data visualization: linear methods Ward: chapter 8 lab3 see above
10/7 High-D data visualization: linear methods Ward: chapter 8   see above
10/12
no class (Fall break)      
10/14
Interaction Ward: chapter 11   interact
10/19
Visual analytics     VA
10/21 Tasks, VA design, and evaluation     VAdesign
10/26
Visualization of hierarchies Ward: chapter 9 lab4 hierarchies
10/28
Midterm      
11/2
Time-varying and streaming data Ward: chapter 7   timeVar
11/4
Maps and geospatial visualization Ward: chapter 6   maps
11/9
Medical and scientific visualization Ward: chapter 5   medSciVis
11/11
Volume visualization: general     volViz
11/16
Volume visualization: transferfunction     see above, illum
11/18
Scientific visualization     sciVis
11/23
Illustrative rendering ImageVis3D Tutorial lab5 illus
11/25
no class (Thanksgiving)      
11/30
Memorable visualizations, visual embellishments     tufte
12/2
Infographics design     infographics
12/9
Final exam (8:30-11:00 pm)