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ATI's Exploring Data: Visualization course


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Summary:

    Technical Training Short On Site Course Quote

      Visualization of data has become a mainstay in everyday life. Whether reading the newspaper or presenting viewgraphs to the board of directors, professionals are expected to be able to interpret and apply basic visualization techniques. Technical workers, engineers and scientists, need to have an even greater understanding of visualization techniques and methods. In general, though, the basic concepts of understanding the purposes of visualization, the building block concepts of visual perception, and the processes and methods for creating good visualizations are not required even in most technical degree programs. This course provides a “Visualization in a Nutshell” overview that provides the building blocks necessary for effective use of visualization.
      View course sampler

    Tuition:

    Instructors:

      Ted Meyer has worked with the National Geospatial-Intelligence Agency (NGA), NASA, and the US Army and Marine Corps to develop systems that interact with and provide data access to users. At the MITRE Corporation and Fortner Software he has lead efforts to build tools to provide users improved access and better insight into data. Mr. Meyer was the Information Architect for NASA’s groundbreaking Earth Science Data and Information System Project where he helped to design and implement the data architecture for EOSDIS.

      Dr. Brand Fortner, an astrophysicist by training, has founded two scientific visualization companies (Spyglass, Inc., Fortner Software LLC.), and has written two books on visualization (The Data Handbook and Number by Colors, with Ted Meyer). Besides his own companies, Dr. Fortner has held positions at the NCSA, NASA (where he lead the HDF-EOS team), and at JHU/APL (chief scientist, intelligence exploitation group). He currently is research professor in the department of physics, North Carolina State University.

      Contact these instructors (please mention course name in the subject line)

    What you will learn:

    • Decision support techniques: which type of visualization is appropriate
    • Appropriate visualization techniques for the spectrum of data types
    • Cross-discipline visualization methods and “tricks”
    • Leveraging color in visualizations
    • Use of data standards and tools
    • Capabilities of visualization tools

      This course is intended to provide a survey of information and techniques to students, giving them the basics needed to improve the ways they understand, access, and explore data.

    Course Outline:

    • Overview
      • Why Visualization?
        • The Purposes for Visualization: Evaluation, Exploration, Presentation

    • Basics of Data
      • Data Elements - Values, Locations, Data Types, Dimensionality
      • Data Structures - Tables, Arrays, Volumes
      • Data – Univariate, Bivariate, Multi-variate
      • Data Relations – Linked Tables
      • Data Systems
      • Metadata – Vs. Data, Types, Purpose

    • Visualization
      • Purposes – Evaluation, Exploration, Presentation
      • Editorializing – Decision Support
      • Basics – Textons, Perceptual Grouping
      • Visualizing Column Data – Plotting Methods
      • Visualizing Grids
        • Images, Aspects of Images, Multi-Spectral Data
        • Manipulation, Analysis, Resolution, Intepolation
      • Color – Perception, Models, Computers and Methods
      • Visualizing Volumes – Transparency, Isosurfaces
      • Visualizing Relations – Entity-Relations & Graphs
      • Visualizing Polygons – Wireframes, Rendering, Shading
      • Visualizing the World – Basic Projections, Global, Local
      • N-dimensional Data – Perceiving Many Dimensions
      • Exploration Basics – Linking, Perspective and Interaction
      • Mixing Methods to Show Relationships
      • Manipulating Viewpoint – Animation, Brushing, Probes
      • Highlights for Improving Presentation Visualizations
      • Color, Grouping, Labeling, Clutter

    • Data Access – Standards and Tools
      • Data Standards – Overview, Purpose, Why Use?
      • Overview of Popular Standards
        • Grid/Image Standards - DTED, NITF, SDTS
        • Science Standards
        • SQL and Databases
        • Metadata - PVL, XML

    • Tools for Visualization
      • APIs & Libraries
      • Development Enviroments
        • CLI
        • Graphical
      • Applications
      • Which Tool?
      • User Interfaces

    • A Survey of Data Tools
      • Commercial
      • Shareware & Freeware

    
    
    Tuition:

      Tuition for this three-day course is $1740 per person at one of our scheduled public courses. Onsite pricing is available. Please call us at 410-956-8805 or send an email to ati@aticourses.com.

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