Spark, Hadoop, and Snowflake for Data Engineering
Completed by FHEREEN NISHA
May 24, 2026
29 hours (approximately)
FHEREEN NISHA'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: Data Integration
- Category: Data Processing
- Category: Snowflake Schema
- Category: Data Pipelines
- Category: Big Data
- Category: PySpark
- Category: Data Transformation
- Category: MLOps (Machine Learning Operations)
- Category: Python Programming
- Category: Model Deployment
- Category: Data Quality
- Category: Data Architecture
