Spark, Hadoop, and Snowflake for Data Engineering
Completed by LENA CHRISPIN FERNANDEZ
October 21, 2024
29 hours (approximately)
LENA CHRISPIN FERNANDEZ'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 Integration
- Category: Data Warehousing
- Category: Data Quality
- Category: Big Data
- Category: Data Pipelines
- Category: Data Processing
- Category: DevOps
- Category: Snowflake Schema
- Category: Model Deployment
- Category: Databricks
- Category: MLOps (Machine Learning Operations)
- Category: Distributed Computing
