Spark, Hadoop, and Snowflake for Data Engineering
Completed by ELMEHDI KARTASSI
June 9, 2024
29 hours (approximately)
ELMEHDI KARTASSI'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 Warehousing
- Category: Data Integration
- Category: Data Pipelines
- Category: Data Quality
- Category: Big Data
- Category: Model Deployment
- Category: Snowflake Schema
- Category: Data Processing
- Category: DevOps
- Category: PySpark
- Category: Distributed Computing
- Category: MLOps (Machine Learning Operations)
