Course Details

  • Course Number: 16:198:526
  • Course Type: Graduate
  • Semester 1: Spring
  • Credits: 3
  • Description:

    This class is a foundational class for the newly created Professional Master in Data Science within the Computer Science Department

  • Category: B (M.S.), B (Ph.D.)
  • Topics:

    Visual Analytics History[Week 1],

    Building blocks and Inherent Scientific Challenges [Week 2]

    Data Management for Visual Analytics [Week 3]

    Data with Spatial and Temporal Components [Week 4 and 5]

    Scalable and Compos sable Visualizations [Week 6]

    Infra Structural and Language Issues (Hadoop, MapReduce, R, Python)[Week 7, 8, 9 ]

    Evaluation Methodologies and Challenges [Week 10],

    Data Ethics [Week 11]

    Privacy and Security [Week 12]

    Data Sharing and Data Provenance [Week 13]

    Gala Presentation[Week 14].

    Course Material: 

    • Reference Materials

                     VisMaster-book

                     The electronic version of this book is available from the Eurographics Digital Library at http://diglib.eg.org

    • Selected papers from the literature on

             – Algorithmic Analytics, Visualization and Computer Human Interaction.

             – Data Ethics, Privacy, Security, Sharing, Provenance

  • Expected Work: Students in this class will become proficient with the major techniques and systems for algorithmic data analysis, exploration, visualization, interaction and summarization. A competitive group project will be completed that incorporates all the major facets of computer-human interface development. 
  • Notes:

    Objective: Expose and train students in all the facets of computer-user interface development

    Guiding evaluation principles will be: the “value” of the extracted information from a variety of data sets at different scales, the methods and models used, interface interactivity, and the final application usefulness.

    Grading:

    1. Bi-Weekly Homeworks 15%
    2. Midterm Exam 15%
    3. Mid Project Draft 20%
    4. Final Project Demo 50% – Evaluated by a Faculty-Industry Panel