- Course Number: 16:198:526
- Course Type: Graduate
- Semester 1: Spring
- Credits: 3
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.)
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].
- Reference Materials
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.
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.
- Bi-Weekly Homeworks 15%
- Midterm Exam 15%
- Mid Project Draft 20%
- Final Project Demo 50% – Evaluated by a Faculty-Industry Panel