Spark, Hadoop, and Snowflake for Data Engineering
Completed by Ratko Nikolić
January 16, 2024
29 hours (approximately)
Ratko Nikolić'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 Pipelines
- Category: Big Data
- Category: Data Integration
- Category: Databricks
- Category: Model Training
- Category: Apache Spark
- Category: Distributed Computing
- Category: MLOps (Machine Learning Operations)
- Category: Data Architecture
- Category: SQL
- Category: Data Transformation
- Category: Data Quality
