Ultimate AWS Data Engineering Bootcamp - 15 Real-World Labs
Key Takeaways
Builds real-world data engineering projects using AWS tools and services
Original Description
This course features Coursera Coach!
A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.
This course provides hands-on experience with essential AWS data engineering tools and techniques. You’ll work on real-world projects using services like Redshift, DynamoDB, Athena, Glue, Kinesis, and Step Functions to build data pipelines, automate workflows, and process data at scale. Through labs, you'll learn to develop batch and real-time data processing solutions, build scalable datalakes, and implement event-driven pipelines for e-commerce.
Ideal for individuals with basic data engineering, cloud services, and programming knowledge, this course takes you through 15 labs to master AWS data engineering practices. Familiarity with AWS tools is beneficial but not required.
By the end, you’ll have the skills to tackle complex data engineering tasks and deploy cloud-based solutions confidently.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Data Warehousing
View skill →Related Reads
📰
📰
📰
📰
I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer
Towards Data Science
JuiceFS Sync for PB-Scale Data Transfers: Resumable Sync, Encryption, and Bandwidth Control
Dev.to AI
How Airflow is using AI to make data engineering more resilient, not more complex
Medium · AI
What Can We Do When Memory Becomes the New Bottleneck in Data Engineering?
Towards Data Science
🎓
Tutor Explanation
DeepCamp AI