Data powers everything from advanced analytics to data science, machine learning, large language models, and generative AI.

But data is useless until it can be harnessed.

Data engineering is about building systems to do exactly that. Data Engineers wrangle, manipulate, and transform data so it can be used for training AI, generating predictive analytics, and making critical business decisions. Without data engineering, none of this is even possible.

In this course, you'll take your first steps with data engineering. You'll build a serverless data pipeline and apply the core principles of all good data engineering work: efficiency, automation, and scalability.

You'll gain hands-on experience with:

- Serverless data ingestion

- Automated workflow orchestration for ETL (extract, transform, load)

- Advanced SQL strategies for transforming and wrangling data

- Visualizing data for analytics and business intelligence

- Creating and automating data quality checks

Throughout the course, you'll leverage the power of cloud technologies using Amazon Web Services (AWS), the most popular cloud environment.

To be ready to take this course, you should have some SQL and Python knowledge.

For a full breakdown of who the course is for and what you'll learn, check out the course schedule and syllabus below.