About This Domain
Domain 2 — ML Model Development — accounts for 26% of the MLA-C01 certification exam. This domain evaluates your understanding of selecting model types and algorithms for classification, regression, clustering, forecasting, and anomaly detection, configuring sagemaker training jobs, built-in algorithms, custom containers, and distributed training, evaluating models with appropriate metrics and diagnosing overfitting or underfitting, and related concepts. Domain 2 covers selecting ML approaches, training models, tuning hyperparameters, analyzing model performance, and managing versions. 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
- Selecting model types and algorithms for classification, regression, clustering, forecasting, and anomaly detection
- Configuring SageMaker training jobs, built-in algorithms, custom containers, and distributed training
- Evaluating models with appropriate metrics and diagnosing overfitting or underfitting
- Running hyperparameter tuning jobs and selecting objective metrics
- Registering and versioning model candidates for later deployment
Key AWS Services in This Domain
Study Strategy for Domain 2
This domain represents 26% 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 2
Match the metric to the business problem: precision/recall for imbalanced classification, RMSE for regression, and AUC for ranking quality.
If training is expensive and interruptible, managed spot training is often the cost-aware answer.
Use hyperparameter tuning when the model approach is chosen but performance needs systematic improvement.
Model versioning and approval belong in the model registry, not in ad hoc file names.
Frequently Asked Questions
How many questions on the MLA-C01 exam come from Domain 2?
Domain 2 (ML Model Development) makes up 26% of the MLA-C01 exam. The exam has 65 scored questions, so approximately 17 questions will come from this domain.
What services should I focus on for Domain 2?
The key services for this domain include SageMaker, Model Training, ML Algorithms, Model Evaluation, Hyperparameter Tuning, Bedrock, ML Cost Optimization. Make sure you understand how each service works, its use cases, and how they integrate with one another.
How should I prepare for ML Model Development 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 2 Questions
Test your knowledge of ML Model Development with practice questions from our MLA-C01 question bank.
Start Practice Quiz →