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Course Schedule:

Date
Topic
Suppl. Reading (Chapters)
Labs Handouts
01/24 Intro and procedures     intro
01/25 Basic tasks Aggarwal: 1.1-3, 2.1-2   basicTasks
01/31 D3 intro see links inside presentation lab1 D3intro
02/02 Data and representation Aggarwal: 2.3   dataRep
02/07 Data reduction Aggarwal 2.4.1.1, 6.3.1   dataRed
02/09 Snow day (no class)    
02/14 Perception and cognition Ware: chapters 2-4   perception
02/16 Design and Aesthetics Ware:: chapter 4, Munzner: chapter 5   design
02/21 Dimension Reduction Aggarwal 2.4.3.1   dimRed PCA-Tutorial
02/23 Principal Component Analysis Aggarwal 2.4.3.1   on-PCA-loadings
02/28 Cluster analysis Aggarwal 6.4-5 lab 2 clustAna
03/02 Correspondance analysis Aggarwal 6.4-5   see above
03/07 Spatial data: medical and science

 

  medSci
03/09 Volume visualization Engel: chapter 1, 4.1-3, 5.1-6, 7.1-2, 10.1-2   volVis illum
03/14 Spring break (no class)      
03/16 Spring break (no class)      
03/21 Intro to GPU computing NVIDIA CUDA Programming Guide   GPUprimer
03/23 Visualization of science & flow data   lab 3 sciVis
03/28 Midterm I      
03/30 Illustrative rendering   final project npr
04/04 High-dimensional space visualization Munzner: chapters 7, 13   highDVis
04/06 High-dimensional space visualization     see above
04/11 Interaction and information navigation Few: chapter 4   interact
04/13 Hierarchies Munzner: chapter 9, spline lecture (U Wisc.)   hierarchies
04/18 Midterm I discussion    
04/20 Principles of visual analytics Cook Heuer   VA
04/25 Causality and causal structure Wang paper   causality
04/27 Time-varying and streaming data     time
05/02 Midterm II      
05/04 User evaluation techniques, maps     eval maps
05/12 Final project DEMO session 2:15-5 pm