Source: https://www.udemy.com/course/data-engineering-bootcamp-series-1/What you’ll learn
- Understand the Fundamentals of Modern Data Engineering
- Build and Manage Scalable Data Lakes on AWS S3
- Design Star Schema Data Models with Fact & Dimension Tables
- Implement Slowly Changing Dimensions (SCD1 & SCD2)
- Develop ETL Pipelines Using PySpark with Data Quality Checks
- Query and Explore Data Lakes with AWS Athena and Glue Catalog
- Automate Workflows and Pipelines Using Apache Airflow
- Create Custom Airflow Plugins to Manage EMR Spark Jobs
- Apply the WAP (Write-Audit-Publish) Pattern for Production Pipelines
- Implement Data Quality Frameworks and Data Contracts
- Deploy and Monitor Data Pipelines on AWS EMR
- Optimize Data Workflows for Cost, Performance, and Reliability
- Gain Hands-On Experience with Real-World Use Cases
- Prepare for Data Engineering Interviews with Confidence
Requirements
- Basic knowledge of SQL and Python
- Familiarity with Docker and Bash scripting helpful
Download Links
Password: cms.ddpanda.org
