- Database Architecture and Administration
- Data Quality
- Distributed Computing
- Data Integration
- Big Data
- Apache Hadoop
- Data Processing
- PySpark
- Data Pipelines
- Databricks
- SQL
- Apache Spark
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
