Spark, Hadoop, and Snowflake for Data Engineering
Completed by Fan Wu
May 18, 2024
29 hours (approximately)
Fan Wu'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: Snowflake Schema
- Category: DevOps
- Category: Data Processing
- Category: Data Warehousing
- Category: Data Integration
- Category: Distributed Computing
- Category: MLOps (Machine Learning Operations)
- Category: Data Pipelines
- Category: Databricks
- Category: Data Quality
- Category: Model Deployment
- Category: Big Data
