The demand for data science professionals is at an all-time high. Around 22,000 freshers were added to analytics workforce in India this year, an increase of 37% from 2018 according to the data science industry study conducted by Analytics India Magazine and Praxis.
While there is much excitement in the market, there is an equal amount of confusion as well regarding how one should really transition to the field. On one side the expectations of the companies are huge. When we look at the JDs, we see requirements of a ‘rockstar’ full-stack data scientist who knows everything, from statistics to machine learning, from model development to business development.
On the other side, we see educational institutes and training institutes offering a wide spectrum of programs – from comprehensive long duration programs to specific short duration capsules in full time, hybrid and online mode. The candidates aspiring to step into the domain find it hard to demystify the jargon and identify a path suitable for them to upskill themselves and transition to a successful career in the filed. Register for the webinar here.
AIM brings to you two stalwarts – one from the industry and another from academia to give the aspirants clarity about how to make their data science move.
Register for the webinar here.
Your key takeaways from the webinar:
- What are the skills needed to be successful in data science – soft skills and hard skills?
- How does one assess if one is suitable for a career in data science?
- How does one embark on the data science journey?
Date : 24 October 2019 (Thursday)
Time : 7 pm to 8 pm
Speakers for the webinar:
- Shivaram KR
Co-Founder & CEO – Curl Analytics
BE (ECE) RVCoE, MTech (Control & Automation) IIT Delhi
Shivaram has over 12 years of experience in Machine Learning. Algorithm trading strategy (High-Frequency Trading) development has been his forte and he has honed these skills in his stints with Bank of America & Edelweiss Securities. Prior to Founding Curl, Shivaram led a niche quant team at Société Générale, where he worked on applying machine learning to forecasting financial markets, rainfall (alternative data analysis) and many other challenging problems. He has published several papers, on applying Machine Learning to markets.
- Charanpreet Singh
Founder & Director – Praxis Business School Foundation
B.Tech (Mech) IIT Kanpur, MBA University of Iowa
Charanpreet has 30+ years of experience in organisations like British Oxygen, Tata Steel, PwC, HP and Praxis. Prior to founding Praxis, Charanpreet was heading the SMB Sales at HP-Compaq. Prof. Charanpreet Singh is the driving force behind the success of the Praxis Data Science program. He has professional and academic interests in the areas of education, learning, data science and communication and has been a mentor to career aspirants across domains.
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As a thorough data geek, most of Abhijeet's day is spent in building and writing about intelligent systems. He also has deep interests in philosophy, economics and literature.