Spark, Hadoop, and Snowflake for Data Engineering
Completed by Rick Kaptein
January 22, 2024
29 hours (approximately)
Rick Kaptein's account is verified. Coursera certifies their successful completion of Spark, Hadoop, and Snowflake for Data Engineering
What you will learn
Create scalable data pipelines (Hadoop, Spark, Snowflake, Databricks) for efficient data handling.
Optimize data engineering with clustering and scaling to boost performance and resource use.
Build ML solutions (PySpark, MLFlow) on Databricks for seamless model development and deployment.
Implement DataOps and DevOps practices for continuous integration and deployment (CI/CD) of data-driven applications, including automating processes.
Skills you will gain
- Category: PySpark
- Category: Data Processing
- Category: Snowflake Schema
- Category: DevOps
- Category: Data Warehousing
- Category: Data Integration
- Category: Data Pipelines
- Category: MLOps (Machine Learning Operations)
- Category: Distributed Computing
- Category: Databricks
- Category: Data Transformation
- Category: Python Programming
