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Machine Learning:
Using Data for Decisions

Skilfully solve complex business
problems with the power of data

ISB, Hyderabad Campus

INR 1,35,000 plus GST @ 18%

Fee includes food and accommodation at the ISB campus or
at an equivalent facility based on availability.


This programme throws light on various models of Machine Learning and how its applications can be used by companies to help drive business decisions, have better reach and serve their customers better.

Our primary objective is to help you foster the ability to deal with the concepts and mechanics of data analytics and modelling.



R Programming and the fundamentals of various analytical methods

The ability to decide between various analytical methods to optimally solve business problems

Define the key metrics and variables for modelling

Draw insights and inferences from large amounts of data

Text Analytics for Finance | AI, Neural Networks, and Deep Learning


Sanjiv R. Das

is William and Janice Terry Professor of Finance and Data Science, Santa Clara University, Santa Clara, CA. He previously held faculty appointments as Associate Professor at Harvard Business School and UC, Berkeley.

His current research interests include modelling of default risk, machine learning, social networks, derivatives pricing models, portfolio theory and venture capital.

Today, there is a need for turbocharged data-analytics strategies, a new top-team mindset, fresh talent approaches and a concerted effort to break down information silos through machine learning and data analytics.

~ McKinsey & Company - Data Insights

A Vibrant Alumni Network

The ISB CEE has a strong alumni community of more than 40,000 business leaders, senior professionals and entrepreneurs. Being a part of the alumni network ensures you get access to premium learning events, speaker sessions and conferences, not to mention, the opportunity to network with successful alumni across diverse industries.

Centre for Executive Education, Indian School of Business | | Ph: +91 40 2300 7041/42 | Fax: +91 40 2300 7040

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