M.Tech I Year II Semester (R22)
Basic Programming.
After completion of course, students would be able to:
Introduction: Data Analytics, Data Visualization, Data and Tasks, Data Types, Dataset Types, Spatial Data-Scivis and Infovis, Static Graphics, Data Visualization Through Their Graph Representations Interaction Techniques - Brushing and Linking, Dynamic Queries, Animation, Trees and Networks, Radial Layouts, Tree Maps, Linear Layouts, Maps, Cartograms, Symbol Maps, Flow Maps, Real-Time Maps
High Dimensional Data Visualization, Filtering, Parallel Coordinates, Mosiac Plots, Time Series, Aggregation Text Visualization, Document Visualization, Images & Video, Selecting Video Points, Zooming and Panning, Perception, Visual Channels. Weber's Law, Visual Channel Rankings
Color Processing: Color Spaces, Color Aesthetics, Colors for Visualization, Cognition, Looking vs. Seeing, Image Gist, Gestalt Principles, Visual Attention, Visual Working & Long-Term Memory
Advanced Analytics: Introduction to Tableau, Adding Data Sources in Tableau, Creating Data Visualizations, Aggregate Functions, Table Calculations, Maps, Trends, Trend Lines, Forecasts, Clusters Analysis, Dashboards and Other Statistical Tools
Data Visualization System: Visual Storytelling, Messaging, Effective Presentations, Design for Information Visualization and Arts, Visualization Systems- Database Visualization
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