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Bootstrap Data Science

Designing your Data Product Strategy

Date: 1700 - 1900 on 21st Dec 2017
Location: 91Springboard, 7th Block, Koramangala

There’s a lot of hype around data science, machine learning and deep learning - and for good reason. They have transformed many businesses and impacted lives of many consumers. Amit and Bargava mentor companies (startups as well as enterprises) to setup and scale data science teams in-house. They use real-life case studies to talk about how Data Science can be leveraged as a key differentiator at a product-focused company.

The talk primarily covers the following:

When and how to start thinking about data science?
How should the team be structured?
What are the skills required?
How to bootstrap it into the product?
What to do when there is little data?
Some thoughts and open discussion around tools and deployment strategies (including demo).

Speakers

Amit Kapoor teaches the craft of telling visual stories with data. He conducts workshops and trainings on Data Science in Python and R, as well as on Data Visualisation topics. His background is in strategy consulting having worked with AT Kearney in India, then with Booz & Company in Europe and more recently for startups in Bangalore. He did his B.Tech in Mechanical Engineering from IIT, Delhi and PGDM (MBA) from IIM, Ahmedabad. You can find more about him at amitkaps.com and tweet him at @amitkaps.

Bargava Subramanian is a Machine Learning/Deep Learning engineer based out of Bangalore, India. He currently mentors early stage startups in their data science journey. Bargava has 14 years’ experience delivering business analytics solutions to investment banks, entertainment studios, and high-tech companies. He has given talks and conducted numerous workshops on data science, machine learning, deep learning, and optimization around the world. Bargava holds a master’s degree in statistics from the University of Maryland at College Park. He is an ardent NBA fan. You can find more about him at bargava.com and tweet him at @bargava.