Spark, Hadoop, and Snowflake for Data Engineering
Completed by Trisha Sen
April 5, 2025
29 hours (approximately)
Trisha Sen'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: MLOps (Machine Learning Operations)
- Category: Data Transformation
- Category: Distributed Computing
- Category: Python Programming
- Category: Data Architecture
- Category: Apache Hadoop
- Category: Apache Spark
- Category: Data Quality
- Category: Model Deployment
- Category: Data Processing
- Category: Snowflake Schema
