Spark, Hadoop, and Snowflake for Data Engineering
Completed by Denis Mironov
April 3, 2024
29 hours (approximately)
Denis Mironov'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: Data Warehousing
- Category: Data Integration
- Category: Data Pipelines
- Category: Data Quality
- Category: Big Data
- Category: Data Processing
- Category: Snowflake Schema
- Category: DevOps
- Category: Databricks
- Category: MLOps (Machine Learning Operations)
- Category: Distributed Computing
- Category: Model Deployment
