Spark, Hadoop, and Snowflake for Data Engineering
Completed by Gzim Vrellaku
April 13, 2024
29 hours (approximately)
Gzim Vrellaku'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 Pipelines
- Category: Data Quality
- Category: Big Data
- Category: Data Warehousing
- Category: Data Integration
- Category: Data Processing
- Category: Snowflake Schema
- Category: DevOps
- Category: Python Programming
- Category: Data Architecture
- Category: SQL
- Category: Model Training
