Spark, Hadoop, and Snowflake for Data Engineering
Completed by José de Jesús Ortiz Rangel
June 24, 2024
29 hours (approximately)
José de Jesús Ortiz Rangel'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: MLOps (Machine Learning Operations)
- Category: Distributed Computing
- Category: Databricks
- Category: Data Quality
- Category: Big Data
- Category: Data Pipelines
- Category: Data Processing
- Category: Snowflake Schema
- Category: DevOps
- Category: Data Transformation
- Category: Python Programming
- Category: Data Architecture
