Spark, Hadoop, and Snowflake for Data Engineering
Completed by Nela Brockington
January 11, 2024
29 hours (approximately)
Nela Brockington'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 Deployment
- Category: Data Warehousing
- Category: Data Integration
- Category: Big Data
- Category: Data Pipelines
- Category: Python Programming
- Category: Apache Spark
- Category: Data Processing
- Category: Distributed Computing
- Category: MLOps (Machine Learning Operations)
- Category: Apache Hadoop
- Category: Data Quality
