April 20 - 22, 2017
This course introduces R – a language and environment for Statistical Computing and Visualisation. In recent years, R has become very popular due its open source cross-platform nature, robust package repository and strong graphics capabilities. During the course, one will not only learn about basics of R, but also about techniques of data acquisition and processing. Course will also cover in detail the features of R related to data analysis and visualisation.
May 18 - 20, 2017
The course aims to provide learners an understanding of the methods for text analytics. It will cover major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making. The techniques will include Named Entity Recognition, Sentiment Analysis and Text Categorization among others. Learners will also be introduced to various open source utilities for developing text analytics applications.
June 15 - 17, 2017
The course covers various methods of Predictive Analytics and Recommender Systems drawn from Statistics, Data Mining, and Machine Learning. We will discuss popular algorithms in the domain and their use in various applications. The course emphasizes hands-on approach for better understanding of the techniques used in the domain. During the course, mainly open-source tools will be used for illustrations and lab.