Let's Talk: Data Science



For startups, data science is relevant as the CEO and CTO needs to be able to capture information from their core users at the earliest stage, to identify key features that users love, and address problems that hinder users from using their product.

For corporates, the huge volume of data exceeds the capability and capacity of their existing data management workflow, and data science will assist their engineers to revise and enhance their current data processing strategy.


According to The New York Times, data science “promises to revolutionize industries from business to government, health care to academia.” As data accumulates, organizations are hiring individuals with the expertise to find meaning in the numbers and drive positive business decisions based on what they learn. It is estimated that by 2018, 4 million to 5 million jobs in the United States will require data analysis skills, and a recent study from the McKinsey Global Institute found “a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge (for the U.S.).” Based on the number of job openings, median base salary and career opportunities, Glassdoor has ranked data scientist as the “Best Job in America” for 2017 and beyond.

1. EDA with car insurance data using R
2. Sentiment Analysis with python
3. Decision Tree with python
4. Time Series with ARIMA using R


9:00am - 9:30am: Arrivals and registration
9:30am - 12pm: Data Science by Tarun Sukhani
12:00pm - 12:30pm: Qna till end


Tarun Sukhani has 16 years of both academic and industry experience as a data scientist over the course of his career. Starting off as an EAI consultant in the USA, Tarun was involved in a number of integration/ETL projects for a variety of Fortune 500 and Global 1000 clients, such as BP Amoco, Praxair, and GE Medical Systems.

While completing his Master's degree in Data Warehousing, Data Mining, and Business Intelligence at Loyola University Chicago GSB in 2005, Tarun also worked as a BI consultant for a number of Fortune 500 clients at Revere Consulting, a Chicago-based boutique IT firm focusing on Data Warehousing/Mining projects. Tarun continues to work within the BI space, most recently focusing his time on Deep/Reinforcement Learning projects within the Fintech sector.

Tarun has also worked on parametric statistical modeling as well within the Data Science and Big Data Science space, using tools such as SciPy in Python and R and R/Hadoop for Big Data projects.

Fri Mar 23, 2018
9:30 AM - 12:00 PM MYT
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