Spark, Hadoop, and Snowflake for Data Engineering
Completed by Anis Bourbia
March 22, 2026
29 hours (approximately)
Anis Bourbia'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: Snowflake Schema
- Category: DevOps
- Category: Data Processing
- Category: Data Integration
- Category: Data Warehousing
- Category: Big Data
- Category: Data Pipelines
- Category: Python Programming
- Category: Databricks
- Category: MLOps (Machine Learning Operations)
- Category: Distributed Computing
- Category: Data Architecture
