- Data Transformation
- Distributed Computing
- Apache Spark
- Apache Hadoop
- Data Processing
- Big Data
- PySpark
- MLOps (Machine Learning Operations)
- Data Warehousing
- Databricks
- Database Architecture and Administration
- SQL
Spark, Hadoop, and Snowflake for Data Engineering
Completed by Ben Goren
February 16, 2024
29 hours (approximately)
Ben Goren'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
