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- Total Questions: 241 Q&A's
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- Multiple Choice Questions: 7 Q&A's
- Hotspot Questions: 19 Q&A's
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Amazon Web Services MLA-C01 - AWS Certified Associate Practice Exam
- Certification Provider:Amazon Web Services
- Exam Code:MLA-C01
- Exam Name:AWS Certified Machine Learning Engineer - Associate
- Certification Name:AWS Certified Associate
- Total Questions:241 Questions and Answers With Detailed Explanations
- Updated on:Based on the current MLA-C01 exam blueprint. Updated on Sep 29, 2026
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MLA-C01 Question and Answers
90% of Amazon Web Services candidates pass within 2 weeks using only 30 minutes a day.
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A company launches a feature that predicts home prices. An ML engineer trained a regression model using the SageMaker AI XGBoost algorithm. The model performs well on training data but underperforms on real-world validation data.
Which solution will improve the validation score with the LEAST implementation effort?
An ML engineer is using an Amazon SageMaker AI shadow test to evaluate a new model that is hosted on a SageMaker AI endpoint. The shadow test requires significant GPU resources for high performance. The production variant currently runs on a less powerful instance type.
The ML engineer needs to configure the shadow test to use a higher performance instance type for a shadow variant. The solution must not affect the instance type of the production variant.
Which solution will meet these requirements?
An ML engineering team has a data processing pipeline that ingests sensor data from IoT devices into an Amazon S3 bucket. The pipeline then processes the data by using AWS Glue extract, transform, and load (ETL) jobs for ML modeling. The team noticed throttling errors in the ETL jobs. The data ingestion process has also been slower than normal.
What is the cause of the problem?
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Amazon Web Services MLA-C01 Exam Structure and Topic Breakdown
| Domain | Weightage |
|---|---|
| Data Preparation for Machine Learning | 28% |
| ML Model Development | 26% |
| Deployment & Orchestration of ML Workflows | 22% |
| ML Solution Monitoring, Maintenance, & Security | 24% |
The AWS Machine Learning Engineer – Associate (MLA-C01) exam focuses on building and deploying machine learning solutions on AWS, covering six key domains: data ingestion and preparation, exploratory data analysis, feature engineering, model training and evaluation, deployment and MLOps practices, and monitoring, governance, and security. The course develops hands-on skills in selecting appropriate AWS services, optimizing ML pipelines, automating workflows, and ensuring scalable and reliable model performance in production environments. Candidates learn to translate business problems into ML solutions using cloud-native tools and best practices. This certification validates practical, job-ready expertise in machine learning engineering, strengthening career opportunities in data-driven and cloud-focused roles.
Endorsed by Machine Learning Specialists
"Deploying robust ML models requires a deep mastery of feature engineering, SageMaker pipeline architecture, and hyperparameter tuning. This study resource provided the technical precision I needed to pass the MLS-C01 exam with total clarity."
— Tessia, AWS Certified Machine Learning Specialist
"I have rigorously vetted these materials against real-world MLOps standards. The technical depth regarding model evaluation metrics, distributed training, and security for ML workflows is exceptional. An essential guide for any serious ML practitioner."
— Torian, Senior Machine Learning Architect
Expert-Validated AWS Machine Learning Certification Resources.
MLA-C01 FAQs
It is a certification exam that tests your ability to build and manage machine learning solutions on AWS.
Anyone who works with machine learning on AWS or wants to show their skills in cloud-based ML.
It shows you can design, train, and deploy machine learning models using AWS services.
Yes, the exam mostly has multiple-choice and multiple-answer questions.
Yes, AWS updates the exam to match new tools and best practices.
Yes, some questions present scenarios to test practical decision-making skills.
The exam has a fixed time limit, usually around 2 hours.
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