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Data Engineering over Data Science, Understand Why?

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Data engineers build and maintain the systems that allow data scientists to access and interpret data. The role generally involves creating data models, building data pipelines, and overseeing ETL (extract, transform, load). Data scientists build and train predictive models using data after it’s been cleaned. They then communicate their analysis to managers and executives.

Data engineering, in a nutshell, means maintaining the infrastructure that allows data scientists to analyze data and build models. Though the title “data engineer” is relatively new, this role also has deep conceptual roots. 

Here we are going to understand all this in-depth.

In this session you will learn:

  1. Data Industry and Ecosystem

  2. What Is a Data Engineer?

  3. Data Engineer Vs Data Scientist

  4. Growing Demand of Data Engineers

  5. How Do You Become a Data Engineer?

About: Gururajan Govindan

Gururajan Govindan is a Data Science professional and an Intrapreneur with over 7+ of experience working across domains such as  Automobile, Insurance, and Finance. He is known for his expertise in data-driven decision-making. He is currently working on building Data Pipelines and Machine Learning models in the field of  Marketing Analytics.

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About Antwak

Antwak is an experiential learning platform that has 1000+ free, bite-sized professional learning courses in 15+ domains such as CybersecurityDigital MarketingData Engineering powered by 2,500+ experts from 500+ brands & corporates across 30+ countries. 

Antwak offers 16 week LIVE courses powered by the industry’s top professionals. Antwak enables college students and early professionals to get trained on in-demand skills and accelerate their careers in digital-first domains at a fraction of the costs of available alternatives. For more information, visit www.antwak.com

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