Spark, Hadoop, and Snowflake for Data Engineering
Completed by David Custódio
December 17, 2024
29 hours (approximately)
David Custódio'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: Model Training
- Category: Databricks
- Category: Apache Spark
- Category: Snowflake Schema
- Category: DevOps
- Category: MLOps (Machine Learning Operations)
- Category: PySpark
- Category: Distributed Computing
- Category: Data Architecture
- Category: Apache Hadoop
- Category: Model Deployment
- Category: Data Quality
