Amarnath Gupta

 

 


 

Amarnath Gupta is a Research Scientist at the San Diego Supercomputer Center (SDSC) of the University of California San Diego. He leads the Advanced Query Processing Laboratory in the Data and Knowledge Systems group at SDSC. His research interests include scientific data modeling, information integration, multimedia databases and spatiotemporal data management.

Amarnath received his Bachelor of Technology from the Indian Institute of Technology, Kharagpur, a Master of Science in Biomedical Engineering from University of Texas, Arlington, and his Ph.D. (Engineering) degree in Computer Science from Jadavpur University, India.

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Dec 5th 2016

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects.

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Dec 5th 2016

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools.

Average: 3 (3 votes)
Nov 28th 2016

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems.

Average: 4.5 (10 votes)
Nov 28th 2016

This course is for those new to data science.

Average: 5 (1 vote)