Spark, Hadoop, and Snowflake for Data Engineering
Completed by Diego RodrÃguez Ponce
September 13, 2025
29 hours (approximately)
Diego RodrÃguez Ponce'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: Big Data
- Category: Data Quality
- Category: PySpark
- Category: SQL
- Category: Data Pipelines
- Category: Data Processing
- Category: Snowflake Schema
- Category: Apache Hadoop
- Category: Apache Spark
- Category: Databricks
- Category: MLOps (Machine Learning Operations)
- Category: Distributed Computing
