AWS: Feature Engineering Data Transformation & Integrity
Completed by Ming-Un Myron Chang
March 29, 2026
5 hours (approximately)
Ming-Un Myron Chang's account is verified. Coursera certifies their successful completion of AWS: Feature Engineering Data Transformation & Integrity
What you will learn
Apply data cleaning, transformation, and feature engineering techniques to prepare datasets for machine learning.
Recognize methods to detect and reduce bias in data preparation and securely manage PII using AWS tools like DataBrew.
Implement ETL workflows using AWS Glue, Glue Crawlers, and DataBrew for data preparation.
Process large-scale datasets using Apache Spark on Amazon EMR for machine learning workloads.
Skills you will gain
- Category: Model Training
- Category: Data Transformation
- Category: Data Quality
- Category: Feature Engineering
- Category: Data Pipelines
- Category: Data Preprocessing
- Category: Personally Identifiable Information
- Category: Data Validation
- Category: Data Cleansing
- Category: Apache Spark
- Category: Extract, Transform, Load
- Category: Responsible AI
