Spark, Hadoop, and Snowflake for Data Engineering
Completed by Grishma Girish Antad
February 21, 2024
29 hours (approximately)
Grishma Girish Antad'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 Transformation
- Category: Distributed Computing
- Category: Apache Hadoop
- Category: Data Pipelines
- Category: DevOps
- Category: Apache Spark
- Category: Model Deployment
- Category: Data Processing
- Category: PySpark
- Category: Snowflake Schema
- Category: Data Quality
- Category: Data Warehousing
