- Databricks
- Database Architecture and Administration
- DevOps
- MLOps (Machine Learning Operations)
- Data Pipelines
- Data Quality
- Data Integration
- Distributed Computing
- SQL
- Python Programming
- Big Data
- Apache Hadoop
Spark, Hadoop, and Snowflake for Data Engineering
Completed by Minh Nguyen Ngoc Tue
September 24, 2024
29 hours (approximately)
Minh Nguyen Ngoc Tue'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
