Spark, Hadoop, and Snowflake for Data Engineering
Completed by Marie Jane Thompson
January 29, 2024
29 hours (approximately)
Marie Jane Thompson'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 Quality
- Category: Python Programming
- Category: Data Architecture
- Category: SQL
- Category: Model Training
- Category: MLOps (Machine Learning Operations)
- Category: Data Transformation
- Category: Big Data
- Category: Data Pipelines
- Category: Apache Hadoop
- Category: Snowflake Schema
