Enabling Large Scale Data Analytics: From Theoretical Foundations to Practice

IIT Hyderabad is organising a course on "Enabling Large Scale Data Analytics: From Theoretical Foundations to Practice" in Summer 2016. The course will be held at IIT Hyderabad Campus from 13th June to 17th June 2016. The course instructor is Dr. Barna Saha, Assistant Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst.

The course is being offered under the GIAN scheme launched by the Govenment of India.

Update: Registration fees for industry participants have been reduced. Deadline extended till 05 June 2016. Details here.


The amount of data in our world has been exploding at an unforeseeable rate. The increasing volume and detail of information captured by enterprises, and the rise of multimedia, social media, and the Internet of Things are contributing to this exponential growth. Healthcare industries are promising to transform the world through "big" data. The ongoing data deluge is bringing in new opportunities in businesses, finances, and education. As we walk through this digitized age of exploded data, there is an increasing demand to develop unified toolkits for data processing and analysis. In this course our main goal is to lay the mathematical foundation of large scale data processing, develop algorithms and learn how to analyze them.


The primary objectives of the course are as follows:

  1. Exposing participants to the theories behind large scale data processing algorithms
  2. Providing exposure to practical problems and their solutions, and understanding why the solutions work
  3. Enhancing the capability of the participants to perform theoretical analysis with the goal of developing practical algorithms for variety of applications.
  4. To develop an appreciation for current and future challenges of large scale data analytics methods in both theory and practice.


Since good amount of time in the course will be devoted to theoretical aspects of large scale data analytics, the participants are expected to have understanding of basic probability, and general notion of algorithms.