About This Domain
Domain 1 — Data Preparation for Machine Learning — accounts for 28% of the MLA-C01 certification exam. This domain evaluates your understanding of ingesting and transforming structured, semi-structured, and unstructured datasets, cleaning, normalizing, encoding, labeling, and validating data before training, managing datasets in s3 and cataloging them with aws glue and athena, and related concepts. Domain 1 validates your ability to ingest, transform, validate, prepare, and manage data for machine learning model development. To pass this section you need practical knowledge of how these services and patterns work together in real-world architectures.
What You'll Be Tested On
- Ingesting and transforming structured, semi-structured, and unstructured datasets
- Cleaning, normalizing, encoding, labeling, and validating data before training
- Managing datasets in S3 and cataloging them with AWS Glue and Athena
- Creating reusable features and preventing data leakage
- Checking data quality, class imbalance, outliers, and schema drift
Key AWS Services in This Domain
Study Strategy for Domain 1
This domain represents 28% of the total exam, making it a significant scoring area. Balance theoretical study with hands-on practice. Use practice quizzes to identify weak spots and review the topics where you score below 75%.
Exam Tips for Domain 1
Start every data scenario by identifying the source, format, quality issue, and target ML workflow.
Use Glue and Athena for discovery and transformation when the data is already in S3.
Feature leakage is a common trap: do not use information that would not exist at prediction time.
Know when an online feature store is needed for low-latency inference and when the offline store supports training.
Frequently Asked Questions
How many questions on the MLA-C01 exam come from Domain 1?
Domain 1 (Data Preparation for Machine Learning) makes up 28% of the MLA-C01 exam. The exam has 65 scored questions, so approximately 18 questions will come from this domain.
What services should I focus on for Domain 1?
The key services for this domain include Data Preparation, Feature Engineering, Data Quality, S3, AWS Glue, Athena, Feature Store. Make sure you understand how each service works, its use cases, and how they integrate with one another.
How should I prepare for Data Preparation for Machine Learning questions?
Start by reviewing the key topics listed above, then practice with domain-specific questions. Focus on understanding real-world scenarios rather than memorizing facts. Use our practice quizzes to test your knowledge and review explanations for any questions you get wrong.
What's the best order to study the MLA-C01 domains?
Many candidates start with the highest-weighted domains first. For the MLA-C01 exam, the domains in order of weight are: Data Preparation for Machine Learning (28%), ML Model Development (26%), Deployment and Orchestration of ML Workflows (22%), ML Solution Monitoring, Maintenance, and Security (24%). However, start with whichever domain aligns best with your existing experience.
Practice Domain 1 Questions
Test your knowledge of Data Preparation for Machine Learning with practice questions from our MLA-C01 question bank.
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