We are living in a Data Age. Data is being continuously generated and consumed in various formats, and sizes from a number of varied sources. This data can be a big asset if stored, processed and analysed efficiently in real time with the help of intelligent algorithms. There is a growing interest to utilize such data for the improvement of business, health, education, society, etc.
There are many ways to process and analyse such data spanning techniques like data visualisation, text analysis, predictions and recommendations etc. Applications of these techniques can give companies and organisations valuable insights leading to competitive advantage, efficient service delivery and above all customer satisfaction. And so the demand for skilled resources in these fields is growing day by day.
With this view, CDAC, Mumbai is announcing three short-term courses in Data Science and Machine Learning.
Course Dates: April 20 - 22, 2017
Registration Closed[on April 05, 2017]
Course Dates: May 18 - 20, 2017
Registration Open[Last Date: May 03, 2017]
Course Dates: June 15 - 17, 2017
Registration Open[Last Date: June 01, 2017]
April 20 - 22, 2017
Today we live in Data Age. Data is all around us. We continuously generate as well as consume data in various formats, and sizes from number of varied sources
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.