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Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.
Are you curious about a career in data engineering but don’t know where to start? Or perhaps you want more information on what data engineers do before you take the next steps? This four-hour course is an introduction to data engineering and the core concepts, techniques, and tools you need to understand to do the job.
You’ll start by learning the differences between a data engineer and a data scientist (and how they work together) before finding out more about the tools of the trade, specifically talking about cloud computing and parallel computing. By the end of the second chapter, you’ll understand the applications of SQL and NoSQL, using DataFrames, and why parallel computing is so important.
The ETL process is core to a data engineer’s workflow. You will learn how data is extracted, transformed, and loaded to get it ready for analysis and generating insights. At the end of the course, you’ll put all this knowledge into practice by performing and scheduling an ETL process yourself using real-world data.
Our exercises and interactive tests allow you to review and cement your new knowledge, so you’re confident discussing and applying it once you’ve received your Statement of Accomplishment.
This introductory course is part of a data engineering Track, which offers you pathways to improve your understanding of data engineering and a clear set of next steps to becoming a professional data engineer.
Get Started in Data Engineering
Are you curious about a career in data engineering but don’t know where to start? Or perhaps you want more information on what data engineers do before you take the next steps? This four-hour course is an introduction to data engineering and the core concepts, techniques, and tools you need to understand to do the job.
Learn Data Engineering Concepts and Techniques
You’ll start by learning the differences between a data engineer and a data scientist (and how they work together) before finding out more about the tools of the trade, specifically talking about cloud computing and parallel computing. By the end of the second chapter, you’ll understand the applications of SQL and NoSQL, using DataFrames, and why parallel computing is so important.
Perform ETL in Hands-on Exercises
The ETL process is core to a data engineer’s workflow. You will learn how data is extracted, transformed, and loaded to get it ready for analysis and generating insights. At the end of the course, you’ll put all this knowledge into practice by performing and scheduling an ETL process yourself using real-world data.
Our exercises and interactive tests allow you to review and cement your new knowledge, so you’re confident discussing and applying it once you’ve received your Statement of Accomplishment.
This introductory course is part of a data engineering Track, which offers you pathways to improve your understanding of data engineering and a clear set of next steps to becoming a professional data engineer.
