Start your journey to becoming a data engineer and gain the in-demand data engineering skills companies need. In this track, you’ll discover how to build an effective data architecture, streamline data processing, and maintain large-scale data systems.
In addition to working with Python for data engineering tasks, you’ll also grow your language skills as you work with Shell, SQL, and Scala, to create data engineering pipelines, automate common file system tasks, and build a high-performance database.
Through hands-on exercises, you’ll add cloud and big data tools, such as AWS Boto, PySpark, Spark SQL, and MongoDB, to your data engineering toolkit to help you create and query databases, wrangle data, and configure schedules to run your pipelines.
By the end of this track, you’ll have mastered the critical database, scripting, and process skills you need to progress your career and have a firm grasp of Python for data engineering.
Please note this track assumes a fundamental knowledge of Python and SQL.