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Last MLA-C01 English sitting: September 28, 2026

AWS ML Engineer Readiness — Before MLA-C01 Retires

September 28, 2026 is the last day to sit MLA-C01 in English. After that the only option is the GenAI-heavy MLA-C02 beta, with a different objective set. If you have been preparing for MLA-C01, the question is whether you are ready to sit it now — not in November. Take 30 questions, get an instant readiness score, and see exactly which domains would cost you marks.

One question at a time, explained as you go · no sign-up

Instant resultsTopic breakdownWeak area detectionPass likelihood

What this test covers

AWS has confirmed that the last day to take the Machine Learning Engineer Associate (MLA-C01) exam in English is September 28, 2026. Registration for the replacement MLA-C02 beta opened September 1, and it adds substantial generative AI, foundation model, Bedrock, and RAG coverage that MLA-C01 does not test. That leaves candidates mid-prep with a decision: sit the exam you studied for while you still can, or restudy for a broader objective set. This free readiness check covers what MLA-C01 actually tests — SageMaker workflows, ML pipelines and MLOps, model evaluation, and the statistical fundamentals underneath them — so you can answer that question with a score instead of a guess. Score 85+ and you are ready to book. Below 70, the AI Report ($19) maps your weak domains to a study plan sized to the days you have left. To be clear about what is measured: this is not weighted to the MLA-C01 or MLA-C02 blueprint. It draws Examifyr's data science bank, so the score reads the ML fundamentals the exam assumes rather than predicting a result.

  • SageMaker — training jobs, endpoints, model deployment and inference
  • ML Pipelines & MLOps — feature engineering, orchestration, CI/CD for models
  • Model Evaluation — precision/recall, ROC-AUC, cross-validation, bias-variance
  • Monitoring & Retraining — drift detection, model registry, versioning
  • Data Preparation — Glue, feature stores, missing data, feature scaling
  • Statistics & Probability — distributions, hypothesis testing, A/B testing
  • Security & Cost — IAM for ML workloads, instance selection, inference cost

How it works

01

Pick your difficulty

Choose Easy, Medium, or Full test depending on where you are in your learning.

02

Answer questions

One question at a time. Click an answer and get instant feedback with a full explanation.

03

Get your score

See your readiness score (0–100), pass likelihood, and a topic-by-topic breakdown.

Frequently asked questions

Should I take MLA-C01 before September 28, or wait for MLA-C02?
If you have been preparing for MLA-C01 and score 70 or above on this check, sitting it before September 28, 2026 is usually the better move — you already match its objective set, and the certification you earn stays valid regardless of the exam being retired. If you score below 70, you likely will not close the gap in time, and studying directly for MLA-C02 avoids preparing twice for two different objective sets.
What changes in the MLA-C02 beta?
MLA-C02, whose beta registration opened September 1, 2026, keeps the core ML engineering content but adds significant generative AI coverage: foundation models, large language models, Amazon Bedrock, retrieval-augmented generation, and agentic AI patterns. Candidates who prepared only for MLA-C01 will find these sections unfamiliar. As a beta exam it also has a longer wait for results.
Does passing MLA-C01 before it retires still count?
Yes. A certification earned from the MLA-C01 exam remains valid for its full three-year term. Exam retirement affects who can sit the exam going forward, not credentials already earned.
How many questions are in this readiness check?
The full test (Hard mode) has 30 questions across 7 topics covering ML pipelines, model evaluation, statistics, and data preparation. Easy mode focuses on foundational concepts; Hard mode adds trade-off and scenario-style questions closer to exam framing.
What score means I'm ready?
A score of 85–100 places you in the Exam Ready band. 70–84 is Almost Ready — targeted study on your weak domains should close the gap in 1–2 weeks. Below 70, the AI Report ($19) identifies exactly which 2026 exam objectives to prioritise and builds a personalised 14-day study plan.
Are these the actual MLA-C01 exam questions?
No. These are original questions covering the machine learning engineering, model evaluation, and statistics topics that MLA-C01 tests — not real exam items, which AWS does not publish. Use the score as a diagnostic of your grasp of the underlying material, not as a simulation of the exam interface or its exact question mix. The same fundamentals carry over to MLA-C02 and to ML engineering interviews.
Is this free?
Completely free — no account or credit card required. After the test you can optionally purchase the AI Report ($19) for a personalised study plan mapped to your weak areas and the 2026 exam objectives.

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