Spark, Hadoop, and Snowflake for Data Engineering
Completed by Gopal Cheruku
May 28, 2026
29 hours (approximately)
Gopal Cheruku'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: Databricks
- Category: Apache Spark
- Category: Distributed Computing
- Category: Data Integration
- Category: Data Transformation
- Category: Python Programming
- Category: MLOps (Machine Learning Operations)
- Category: Data Quality
- Category: Model Deployment
- Category: Model Training
- Category: Data Processing
- Category: Snowflake Schema
