Spark, Hadoop, and Snowflake for Data Engineering
Completed by Casey Dinan
May 18, 2024
29 hours (approximately)
Casey Dinan'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: DevOps
- Category: Apache Spark
- Category: Python Programming
- Category: Model Training
- Category: Data Pipelines
- Category: Model Deployment
- Category: Data Architecture
- Category: Data Processing
- Category: PySpark
- Category: Apache Hadoop
- Category: Data Warehousing
