The AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam is a must for professionals looking to validate their skills in building, training, and deploying machine learning solutions on AWS. This certification demonstrates your ability to work with real-world ML workflows, from data preparation to model deployment, and is highly regarded in the cloud and AI industry.
Whether you are a data scientist, ML engineer, or AI enthusiast, preparing strategically for this exam is the key to success. This guide provides you with a structured approach, hands-on tips, and resources to ace the MLA-C01 exam in 2026.
1. Understand the Exam Structure
Before diving into study materials, it’s important to understand the exam layout and domain weightings:
Exam Code: MLA-C01
Level: Associate
Duration: 170 minutes
Format: Multiple-choice & multiple-response
Exam Domains:
Data Preparation: 20%
Feature Engineering: 20%
Model Training & Evaluation: 35%
ML Deployment & Operations: 25%
Knowing these weightings helps you focus your study time effectively on the areas that matter most.
2. Master Key AWS Services
The MLA-C01 exam tests your ability to use AWS services in real-world machine learning scenarios.
Focus on hands-on experience with:
- Amazon SageMaker: Training, tuning, and deploying models
- AWS Glue: Data extraction, transformation, and loading (ETL)
- AWS Lambda: Automating ML workflows
- Amazon S3: Storage for datasets and model artefacts
- CloudWatch / Step Functions: Monitoring and orchestration
Gaining practical experience in these services is essential for both the exam and real-world ML engineering.
3. Take Practice Questions
Practising with real exam-style questions is one of the best ways to prepare. It helps you understand the question format, difficulty level, and scenario-based problems.
You can start with free MLA-C01 practice questions here: AWS Certified Machine Learning Engineer Associate Exam – Free Questions.
Regular practice builds confidence and helps identify areas that need extra focus.
4. Use a Study Tracker
Tracking your resources and progress is crucial for structured preparation. Use your Google Stack resource sheet to organise notes, links, and practice questions in one place: Google Stack Resource Sheet.
A study tracker ensures you cover all exam domains systematically and avoid missing important topics.
5. Build a Hands-On Study Plan
Consistency is key. Here’s a sample study plan for MLA-C01 preparation:
Daily: Hands-on exercises in SageMaker, Glue, and Lambda
Weekly: Review key ML concepts, AWS best practices, and domain-specific study notes
Practice Tests: Simulate exam conditions using scenario-based questions
Hands-on practice ensures that you can confidently apply ML concepts in the AWS ecosystem.
6. Key Tips for Exam Day
- Read all questions carefully, especially scenario-based ones.
- Allocate roughly 2–3 minutes per question.
- Review your answers if time permits.
- Stay calm and manage your time efficiently.
Following these tips, along with consistent preparation, will maximise your chances of passing the AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam.
Conclusion
The MLA-C01 exam is an opportunity to demonstrate your expertise in AWS machine learning services and cloud-based ML workflows. With a structured study plan, hands-on experience, and consistent practice using free questions and your Google Stack, you can confidently prepare for and pass this certification in 2026.
Start your preparation today and take the first step toward becoming a certified AWS Machine Learning Engineer.
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