Spark, Hadoop, and Snowflake for Data Engineering
Completed by Samy Boulos
March 13, 2024
29 hours (approximately)
Samy Boulos'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: Apache Spark
- Category: Apache Hadoop
- Category: PySpark
- Category: Snowflake Schema
- Category: DevOps
- Category: Data Pipelines
- Category: Big Data
- Category: SQL
- Category: Distributed Computing
- Category: Databricks
- Category: Data Integration
- Category: Data Warehousing
