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.
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.
Choose Easy, Medium, or Full test depending on where you are in your learning.
One question at a time. Click an answer and get instant feedback with a full explanation.
See your readiness score (0–100), pass likelihood, and a topic-by-topic breakdown.
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.
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.
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.
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.
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.
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.
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.
Free. No sign-up. Results in under 20 minutes.