Course Library

AWS AI Learning Course

Read one exam-domain lesson, open the matching syllabus branch, then drill MCQs until the distractors are obvious.

  • Tracks 4 AWS AI paths
  • Lessons 18 Exam-domain modules

Data Preparation for Machine Learning (28%)

Select a lesson section play button.

AWS Certified Machine Learning Engineer - Associate (MLA-C01)

Data Preparation for Machine Learning (28%)

This lesson turns the official MLA-C01 outline into a short preparation path. Read it once for orientation, then answer the linked MCQs from the syllabus branch before moving to the next module.

What To Master

Prepare reliable ML data through ingestion, storage, transformation, feature handling, and data quality checks.

Fast Prep Tasks

  1. Ingest and store data for repeatable ML workflows.
  2. Transform, clean, label, and validate data before training.
  3. Engineer and manage features for model training and inference.

AWS Services To Recognize

  • Amazon S3
  • AWS Glue
  • Amazon Athena
  • Amazon SageMaker Data Wrangler
  • SageMaker Feature Store
  • Amazon EMR

Scenario Traps

  • Training before checking quality, leakage, bias, or schema drift.
  • Choosing a database or ETL service without considering scale, format, and downstream training needs.

Speed Drill

After this lesson, open the matching syllabus branch and answer MCQs until you can explain why the wrong options are attractive but not best. Then run a short quiz with this module plus one previous weak module.

Official Source

Use the AWS exam guide as the source of truth for final scope checks: MLA-C01 exam guide.