Cutting Edge Analytics

Start Date: Apr 27, 2020 End Date: May 1, 2020
Last Date for Application: April 13, 2020 Last Date for Early Bird: April 7, 2020
Programme Fee: 120000 INR

Plus, GST

Early Bird Fee: 111600 INR

Plus, GST

The field of analytics is changing at a very fast pace necessitating use of new tools and techniques. Big Data has become a common term and many organizations are keen on benefiting from analysis of such data. Text data, image data, video data, shape data, graph data, location data etc are now being commonly used together for answering complex and difficult questions. Fast streaming data such as those generated by IoT devices such as sensors and GPS devices poses the question of how such data can be analysed accurately and quickly. This requires new skills both in information technology and statistics. In this executive education programme, we will focus on building these advanced skills in executives who have substantial experience in using analytics for making business decisions.

• To equip experienced analytics professionals with new concepts and skills
• To guide these professionals in usage of advanced techniques for better business decisions
• To address the shortage of skilled professionals capable of implementing advanced analytical solutions for Big Data.

Module 1: Analytics with Dependent Data

In management applications dependent data occurs very often. With such data it is important to analyze all the variables together and derive insights from their dependence on one another. Modern multivariate analysis techniques can be used fruitfully to visualize, summarize and draw actionable insights from such data. The techniques covered in this module are Multivariate Regression, Dimensionality Reduction, Cluster Analysis and Multidimensional Scaling

Module 2: Machine Learning Techniques 

In this module we discuss some of the widely used machine learning techniques which have applications for solving problems across different functional areas of management. The techniques covered in this module include Support Vector Machines, Random Forests, Artificial Neural Networks  and Deep Learning Networks

Module – 3: Analytics with Complex Data

In this module we deal with analysis of Complex Data which is at the heart of the “Variety” challenge referred to in Big Data Analytics literature. Modern data comes in a variety of forms both structured and unstructured which cannot be analysed using the tools and techniques of Euclidean data. In this module we introduce the participants with techniques for visualizing and analysing text data, functional data, spatial data, directional data and symbolic data with applications and case studies drawn from different areas of management.

Module – 4: Stream Data analytics

In this module we deal with analysis of data streams which is often referred to as “Velocity” challenge in the Big Data Analytics literature. Such data is continuously accumulated and the underlying data generation process is prone to abrupt changes for various reasons some of which may be unknown to the analyst. In this module we discuss techniques of clustering, classifying and predicting with stream data. 

•    A Graduate or a Post-graduate degree in a relevant subject with strong analytical skills

•    Proficiency in programming in at least one language. An exposure to R software is desired. 

•    Some experience in using analytics for business decision making
 

Faculty Chair

Arnab Laha

Programme Faculty



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