Exam Title: AWS Certified Machine Learning Engineer – Associate
Exam Code: MLA-C02
Certification: AWS Certified Machine Learning Engineer – Associate
Total Questions:
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MLA-C02 is new enough that you’re sitting it during its beta window. AWS opened registration on September 1, 2026, and beta delivery only started on September 29. The exam itself validates something specific: can you actually build, deploy, and monitor ML and generative AI systems in production, not just train a model in a notebook. The credential comes from AWS itself, and this update folds in generative AI, agentic workflows, and foundation models alongside traditional ML for the first time. Dumpsgate’s AWS MLA-C02 practice questions are weighted to match AWS’s published domains, so your prep time tracks where the real exam actually scores you.
The AWS MLA-C02 exam, formally the AWS Certified Machine Learning Engineer – Associate, validates your ability to build, operationalize, deploy, and maintain AI and ML solutions and pipelines on AWS. It covers both traditional ML models and foundation models, not one or the other.
This is the updated version of the exam. AWS added generative AI implementation, agentic workflow orchestration, and foundation model selection and fine-tuning to the scope, while keeping the same four-domain structure as before.
Here’s what sitting the MLA-C02 beta actually involves:
|
Exam Code |
MLA-C02 |
| Certification |
AWS Certified Machine Learning Engineer – Associate |
|
Category |
Associate |
|
Question Format |
Multiple choice and multiple response |
| Total Questions |
65 (50 scored, 15 unscored for future evaluation) |
|
Time Allotted |
170 minutes |
| Passing Score | 720 on a scale of 100 to 1,000 (standard scoring doesn’t apply to the beta version) |
|
Beta Fee |
USD 75 |
| Languages |
English only during the beta |
|
Testing Options |
Pearson VUE testing center or online proctored |
| Validity |
3 years |
Because this is a beta, results typically take up to 5 business days instead of appearing right after you finish, and the unscored questions aren’t identified during the exam.
AWS’s official exam guide splits the MLA-C02 into four domains:
|
Domain |
Exam Weighting |
| Data Preparation for ML and AI |
28% |
|
ML Model and Foundation Model (FM) Development |
24% |
| Deployment and Orchestration of ML and AI Workflows |
24% |
|
Operating, Monitoring, and Securing ML and AI Solutions |
24% |
Data Preparation outweighs any single other domain, and the remaining three sit tied at exactly 24% each.
AWS built this exam for people who already work close to the ML pipeline, including ML engineers, MLOps engineers, LLMOps engineers, data engineers, backend software developers, and data scientists. The recommended background is specific:
AWS is also explicit about what this exam does not expect: designing full end-to-end ML architectures, setting ML strategy, or working deeply across two or more specialized ML domains. That’s reserved for AWS’s Specialty-level credential instead.
There’s no required prerequisite certification for the MLA-C02, and no application review before you register. Since it’s in beta, registration currently runs through AWS’s Certification portal in English only, with additional languages arriving once the exam reaches general availability.
The beta fee for the AWS Machine Learning Engineer Associate is $75 USD, noticeably less than the USD 150 AWS charged for the outgoing MLA-C01. That discount is standard for beta exams and isn’t likely to last. Once MLA-C02 reaches general availability, expect pricing closer to what MLA-C01 charged. If you’re weighing whether to sit the beta now, the lower price is a real incentive, but confirm current pricing on AWS’s certification page before you register, since beta windows close and pricing updates without much notice.
Data Preparation gets the largest share of our question bank, matching where AWS weights it highest. The other three domains still get full, proportional coverage instead of being treated as an afterthought.
Foundation model selection, fine-tuning, RAG architectures, and agentic workflow orchestration are genuinely new to this version of the exam. Our AWS MLA-C02 questions cover that material directly instead of recycling MLA-C01 content that predates it.
Questions walk through real pipeline decisions, choosing a deployment target, debugging a failed training job, tuning an endpoint’s auto scaling, rather than asking you to define a term. That matches how AWS actually writes its exams.
Each AWS Certified Machine Learning Engineer Associate question includes a short explanation of why the correct choice works and why the others don’t. A wrong answer becomes something you understand, not just something you move past.
Every domain and its weighting traces directly back to AWS’s published guide for this specific exam version. Nothing here is carried over from MLA-C01 without being checked against what actually changed.
You get access right after payment, and nothing renews automatically after that. Your payment and personal details are handled securely and never shared with third parties, more detail is in our privacy policy.
We’re tracking AWS’s own exam guide and blog updates as MLA-C02 moves from beta toward general availability, so the question bank keeps pace with any changes AWS makes along the way.
The scenarios reflect real SageMaker and Bedrock work, not textbook summaries. That’s what makes the reasoning behind each answer feel familiar instead of abstract.
Working through a full set of AWS MLA-C02 sample questions before you register shows you exactly which domains need more attention, while the beta fee is still low enough that getting it right the first time matters.
There’s no login window or fixed session. A short block between training runs or a longer evening free, the material’s ready whenever you are.
If the material doesn’t match what we’ve described here, our refund policy gives you a straightforward way to ask for your money back.
Ingest a messy dataset, clean it, transform it, and validate it before feeding it into a training job. Data Preparation carries the most weight on this exam, and hands-on pipeline work beats reading about it every time.
Work through both sides of Domain 2 directly: train a SageMaker model the traditional way, then fine-tune or adapt a foundation model through Bedrock. The exam expects comfort with both, not just one.
Build a basic pipeline that automates deployment to an endpoint, including auto scaling configuration. Deployment and Orchestration rewards infrastructure-as-code familiarity, not manual console clicks.
Orchestrate a basic multi-step AI agent workflow and add observability to it. This is new territory for a lot of candidates coming from MLA-C01-era material, so don’t assume general ML experience covers it.
Set up monitoring to catch drift or degraded performance, then configure access controls around the resources involved. Operating, Monitoring, and Securing rewards this combined exercise more than studying each piece alone.
Work through a set of AWS MLA-C02 mock questions across all four domains, then finish with a full practice test under real-time conditions. That combination shows you honestly which scenarios still trip you up before exam day does.
Here is how Dumpsgate really stacks up against the competition:
| Feature | Dumpsgate | Other Platforms |
| Built from AWS’s current MLA-C02 guide | ✅ Yes | ⚠️ Often still MLA-C01-based |
| Weighted to match the official domain percentages | ✅ Yes | ⚠️ Often spread evenly |
| Covers the new GenAI and agentic content | ✅ Yes | ⚠️ Often missing entirely |
| Explanation behind every answer | ✅ Yes | ⚠️ Often missing |
| Instant access, no subscription | ✅ Yes | ⚠️ Varies |
| Clear, simple refund policy | ✅ Yes | ⚠️ Often unclear |
Sitting an exam during its beta window doesn’t mean the material is any lighter. MLA-C02 folds generative AI and agentic workflows into a role that already covered the full ML lifecycle, and a study plan built around the older MLA-C01 content will leave real gaps.
Dumpsgate’s AWS Certified Machine Learning Engineer Associate practice questions are built around the current guide specifically. Work through data preparation first, since it carries the most weight, then round out the three tied domains with equal seriousness. For more exam practice questions across other AWS certifications, Dumpsgate’s catalog covers the rest of the AWS track too.
It confirms you can prepare data for ML and AI, develop and fine-tune both traditional models and foundation models, deploy and orchestrate ML workflows, and operate, monitor, and secure ML and AI solutions on AWS.
Because it’s in beta. AWS is charging USD 75 during this window, compared to USD 150 for the outgoing MLA-C01, and that discount typically goes away once an exam reaches general availability.
The domain structure stayed the same, but MLA-C02 adds generative AI implementation, agentic AI orchestration, foundation model selection and fine-tuning, and responsible AI practices across both traditional ML and GenAI.
MLA-C02 is a role-based Associate exam for ML and MLOps engineers with around a year of experience. The Specialty exam targets people with two or more years developing, architecting, and running ML workloads, and covers broader ground across data engineering and analysis.
No. AWS doesn’t list a required prerequisite for the MLA-C02.
AWS recommends at least 1 year of experience with SageMaker AI, Bedrock, and related AWS ML services, plus at least 1 year in a related technical role.
AWS hasn’t published a GA date as of this writing. Check AWS’s certification page directly for the latest timeline.
Yes, through the AWS Certification Official Practice Question Set and Official Practice Exam on AWS Skill Builder. Those are useful for getting familiar with question style; Dumpsgate is built for deeper, domain-weighted repetition on top of that.
No. It’s original practice content built around AWS’s published exam guide, styled to reflect the scenario format of the real exam without reproducing it.
Dumpsgate’s MLA-C02 practice questions are weighted to match AWS’s official exam guide, with the heaviest coverage on Data Preparation for ML and AI, and a full explanation behind every answer.
Disclaimer: Dumpsgate is an independent exam preparation platform with no affiliation with or endorsement from Amazon Web Services, Inc. “MLA-C02,” “AWS Certified Machine Learning Engineer – Associate,” and related marks are the intellectual property of Amazon Web Services, Inc. and are referenced here for identification purposes only. All practice questions are original content modeled on AWS’s publicly available exam guide and do not represent actual exam questions. Always verify current certification details, including beta status and pricing, on AWS’s official certification page before registering.
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