Spark, Hadoop, and Snowflake for Data Engineering
Completed by Cuong Doan
September 22, 2024
29 hours (approximately)
Cuong Doan'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: Big Data
- Category: Apache Spark
- Category: Data Pipelines
- Category: Snowflake Schema
- Category: DevOps
- Category: Data Processing
- Category: Data Transformation
- Category: Python Programming
- Category: Data Architecture
- Category: SQL
- Category: Model Training
- Category: Apache Hadoop
