HPTM 6284: Introduction to Big Data Visual Analytics
Course Director: Suresh K. Bhavnani
The accelerated growth and complexity of biomedical data far exceeds our cognitive abilities to exploit it for the prevention, diagnosis, and treatment of diseases. A promising approach to bridge this gap is through the emerging field of visual analytics defined as the “science of analytical reasoning facilitated by interactive visual interfaces." This course provides the theoretical foundations and practical methods related to visual analytics focused towards the analysis and comprehension of large and complex biomedical datasets (e.g., genomic data, and electronic health records). The theoretical foundations will focus on principles related to cognition, computation, and graphic design. The practical methods will focus on hands-on experience in using commercial applications and research prototypes which integrate machine learning with visual analytics, neither requiring knowledge of programming. Through a required project, students will have the opportunity to integrate their theoretical and practical knowledge of big data visual analytics to analyze, comprehend, and present complex patterns in a large biomedical dataset. Application of the visual analytical methods to analyze COVID-19 patient data will be highlighted during the course.
1. Understand the motivation and theoretical foundations underlying visual analytics.
2. Learn how to analyze, comprehend, and present patterns in biomedical data using visual analytics.
Format and Times
Online classes through Zoom will be held twice a week on Tuesdays and Thursdays from 3pm-5pm starting June 30th 2020 for 7 weeks.
Email: Donna Adams For: Institute for Translational Sciences Phone: 21932