AWS has four AI certifications you can earn in October 2026: AI Practitioner (AIF-C01) at $100, Machine Learning Engineer Associate (MLA-C01, now being replaced by MLA-C02), Generative AI Developer Professional (AIP-C01) at $300, and the new AI Business Strategist (AIB-C01), which costs $50 while it is in beta. The Machine Learning Specialty (MLS-C01) is gone: its last exam day was March 31, 2026.
For most people the order is simple. Start with AIF-C01, then take the ML Engineer Associate if you build and run ML models, or AIP-C01 if you build generative AI applications. If you lead AI work but don’t write code, AIB-C01 is the one built for you. Below: every AWS AI certification side by side, the path between them, who each one is for, and how renewal works.
AWS AI certifications at a glance
| Active AWS AI certifications | 4: AI Practitioner (AIF-C01), Machine Learning Engineer Associate (MLA), Generative AI Developer Professional (AIP-C01), AI Business Strategist (AIB-C01) |
|---|---|
| Best first exam | AIF-C01: $100, 90 minutes, 65 questions, 700 to pass |
| Engineer exam | MLA-C01 in English ended September 28, 2026. The MLA-C02 beta ($75) began September 29, 2026 |
| Top AI exam | AIP-C01: Professional level, $300, 180 minutes, 75 questions, 750 to pass |
| Newest | AIB-C01: beta since September 29, 2026 at $50 (standard price $100). It does not test AWS services |
| Retired | Machine Learning Specialty (MLS-C01), last exam day March 31, 2026 |
| Valid for | 3 years |
| Renewing | Pass the latest version with AWS’s 50% recertification discount, or earn a higher AI certification that renews it |
| Prerequisites | No earlier certification required. AWS recommends six months to two years of hands-on experience, depending on the level |
Checked against AWS’s certification pages, exam guides and AWS Training and Certification blog on October 6, 2026.
Every AWS AI certification compared
| Certification | Level | Price | Time | Questions | Passing score | Status |
|---|---|---|---|---|---|---|
| AI Practitioner (AIF-C01) | Foundational | $100 | 90 min | 65 (50 scored) | 700 | Available. The Italian and German versions retire after October 15, 2026 |
| AI Business Strategist (AIB-C01) | Business (new category) | $50 beta, $100 standard | 170 min (beta) | 85 (beta) | 700 | Beta since September 29, 2026 |
| ML Engineer Associate (MLA-C01) | Associate | $150 | 130 min | 65 (50 scored) | 720 | English ended September 28, 2026. Japanese, Korean and Simplified Chinese stay open until MLA-C02 is generally available |
| ML Engineer Associate (MLA-C02) | Associate | $75 beta | 170 min (beta) | 85 (beta) | 720 | Beta since September 29, 2026. AWS’s blog dates general availability to January 14, 2027 |
| Generative AI Developer Professional (AIP-C01) | Professional | $300 | 180 min | 75 (65 scored) | 750 | Available |
| Machine Learning Specialty (MLS-C01) | Specialty | Was $300 | 180 min | 65 | 750 | Retired March 31, 2026 |
Passing scores are scaled scores out of 1,000. Beta numbers (AIB-C01 and MLA-C02) describe the beta only: AWS beta exams carry extra unscored items, and the AIB-C01 exam guide gives 130 minutes for the standard version. If you see the code ME1-C02 when you register, that is the code AWS’s certification page shows for the MLA-C02 beta.
The AWS AI certification path: which order to take them
AWS doesn’t require an earlier certification for any of these: you earn each one by passing its own proctored exam. The AIP-C01 page lists no required certifications (it suggests AI Practitioner, Solutions Architect Associate, ML Engineer Associate or Data Engineer Associate as useful background), and the AIB-C01 page says no other AWS certifications are required. So pick the path by the work you do:
| If you are… | Take this path |
|---|---|
| New to AI, in any role (cloud, IT, development, data or business) | AIF-C01, then decide |
| Building, deploying and running ML models with SageMaker AI and Bedrock | AIF-C01 → MLA-C02 |
| Building production generative AI applications on AWS | AIF-C01 → MLA-C02 (optional) → AIP-C01 |
| Leading AI strategy, product, sales or adoption without writing code | AIB-C01, and add AIF-C01 if you want AWS service knowledge |
| Holding the retired MLS-C01 | MLA-C02 or AIP-C01, depending on whether you run models or build generative AI apps |
One practical reason to follow the builder path in order: higher AWS AI certifications renew the lower ones. Earning the ML Engineer Associate automatically recertifies your AI Practitioner, and passing AIP-C01 renews both (details in the renewal section below).
Who each AWS AI certification is for
AWS Certified AI Practitioner (AIF-C01): the starting point
AWS aims AIF-C01 at anyone exploring AI and ML on AWS, including people in cloud, development, data, IT, AI/ML and line-of-business roles. It is a concepts exam, not a coding exam. The published outline has five domains: Fundamentals of AI and ML (20%), Fundamentals of GenAI (24%), Applications of Foundation Models (28%), Guidelines for Responsible AI (14%), and Security, Compliance, and Governance for AI Solutions (14%). That puts 52% of the scored content on generative AI.
AWS refreshed the exam guide to version 1.1 on April 30, 2026, adding agentic AI, the Model Context Protocol (MCP), context engineering and token-based pricing, and AWS says guide changes reach the live exam about a month after they are published. Study from the current guide: our AIF-C01 study guide, free AIF-C01 practice questions (original questions written from the published outline), 3-week study plan and how long to study for AIF-C01. Weighing it up? See is the AWS AI Practitioner worth it, the full AIF-C01 cost breakdown and AWS AI Practitioner vs Azure AI Fundamentals.
AWS Certified AI Business Strategist (AIB-C01): new for business roles
AWS announced AIB-C01 on September 1, 2026, in a new Business category. It does not assess knowledge of AWS services. AWS names product and program managers, sales and business development, line-of-business leaders, consultants, business analysts and marketing professionals as the audience, and recommends about six months of working with or alongside AI initiatives. No coding is required.
The four domains are AI Fundamentals and Literacy (24%), AI Strategy and Business Value Creation (28%), AI Governance and Responsible AI Leadership (24%), and Business Readiness, Leadership, and AI Transformation (24%). The beta runs 85 questions in 170 minutes, in English and Japanese, for $50. Anyone who earns it by February 15, 2027 also gets an Early Adopter badge.
AWS Certified Machine Learning Engineer Associate (MLA-C01 and MLA-C02)
This is AWS’s hands-on ML exam. AWS recommends at least one year of experience with SageMaker AI, Amazon Bedrock and other ML engineering services, and lists ML engineers, MLOps and LLMOps engineers, data engineers, back-end developers and data scientists as typical candidates.
The exam is mid-swap. The last day to take MLA-C01 in English was September 28, 2026, and the MLA-C02 beta began September 29, 2026 at $75 (85 questions, 170 minutes, English only). AWS’s September 2026 announcement dates general availability of MLA-C02, and the retirement of MLA-C01 in all languages, to January 14, 2027, while the certification page still lists general availability as TBD. AWS kept the four-domain structure (no new domains), but MLA-C02 adds Bedrock and retrieval augmented generation (RAG), agentic AI, foundation model selection and fine-tuning, and responsible AI. If you already hold the certification, it stays active for its full three years.
Everything on what changed is in our MLA-C02 exam guide. To prepare, use the MLA-C02 study guide and MLA-C02 practice questions, or the MLA-C01 study guide and MLA practice questions if you test in Japanese, Korean or Simplified Chinese. Then check the 6-week study plan, the ML Engineer exam cost and whether it is worth it for you.
AWS Certified Generative AI Developer Professional (AIP-C01): the top AI exam
AIP-C01 is AWS’s professional-level generative AI exam and the hardest one on this page by format: 75 questions in 180 minutes, with 750 needed to pass. AWS’s target candidate has two or more years building production-grade applications on AWS or with open-source technologies, plus one year of hands-on generative AI work.
The five domains are Foundation Model Integration, Data Management, and Compliance (31%), Implementation and Integration (26%), AI Safety, Security, and Governance (20%), Operational Efficiency and Optimization for GenAI Applications (12%), and Testing, Validation, and Troubleshooting (11%). The beta ended March 31, 2026, and AWS refreshed the standard exam in March 2026 to cover Amazon Bedrock AgentCore. It is offered in English, Japanese, Korean and Simplified Chinese.
AWS Certified Machine Learning Specialty (MLS-C01): retired
AWS retired MLS-C01 after its last exam day on March 31, 2026. If you hold it, it stays active for three years from the date you earned it, but AWS lists no way to renew it after March 31, 2026. AWS points former MLS candidates to AIF-C01, the ML Engineer Associate, the Data Engineer Associate and AIP-C01. Our MLS-C01 retirement guide covers what to take instead.
How AWS AI certifications renew
Every AWS AI certification is valid for three years, including ones earned on a beta exam. Before it expires, you can renew it these ways (per AWS’s recertification page):
- AI Practitioner (AIF-C01): pass the latest AIF-C01, earn the ML Engineer Associate (which automatically recertifies it), or pass AIP-C01.
- ML Engineer Associate: pass the latest MLA exam, pass AIP-C01, or maintain it on AWS Skill Builder, which adds one year and needs a paid subscription.
- Generative AI Developer Professional (AIP-C01): pass the latest version of the exam.
- AI Business Strategist (AIB-C01): pass the latest version of the exam.
- Recertification exams can be taken with the 50% discount voucher in your AWS Certification Account.
To keep every expiry date in one place, use our free AI certification renewal tracker. For how AWS compares with other vendors, see do AI certifications expire.
What the AWS AI path costs
At list prices, AIF-C01 is $100, AIB-C01 is $100 ($50 during the beta), the ML Engineer Associate is $150 (MLA-C02 is $75 during the beta, and AWS prices Associate exams at $150), and AIP-C01 is $300. The full builder path of AIF-C01, ML Engineer Associate and AIP-C01 comes to $550 at list price, before tax. AWS also sets local-currency prices in Australian dollars, euros, Korean won and Japanese yen.
For a side-by-side with other vendors, see what an AI certification actually costs, or plug your own plan into the AI certification cost calculator.
AWS or Microsoft?
Pick the vendor your employer runs on. If that is Azure, Microsoft’s path is the match: see Microsoft AI certifications. If you are choosing an entry-level cert between the two, compare AWS AI Practitioner vs Azure AI Fundamentals. For every vendor ranked together, see the best AI certifications.
HOW TO // AI is not affiliated with or endorsed by Amazon Web Services. AWS and the certification names on this page are trademarks of Amazon.com, Inc. or its affiliates; we use them descriptively. Our practice questions are original and written from AWS’s published exam guides. Verify current details on the AWS certification pages before you book.
Keep exploring: AIP-C01 study guide · AIP-C01 exam cost · AWS AI Business Strategist (AIB-C01) · generative AI certifications · AI Certification Requirements Index
Related guides
- AWS AI Practitioner (AIF-C01) Study Guide & Cheat Sheet
- AWS ML Engineer Exam Cost (MLA-C01/C02): Price, Passing Score, Retakes
- MLA-C02 Exam Guide: What’s Changing From MLA-C01
- AWS AI Practitioner Exam Cost (AIF-C01): Price, Passing Score, Retakes
- Is the AWS AI Practitioner Worth It in 2026? An Honest Look
Frequently asked questions
What AI certifications does AWS offer?
As of October 2026 AWS offers four: AWS Certified AI Practitioner (AIF-C01), Machine Learning Engineer Associate (MLA-C01, being replaced by MLA-C02), Generative AI Developer Professional (AIP-C01), and the new AI Business Strategist (AIB-C01), which is in beta. The Machine Learning Specialty (MLS-C01) retired on March 31, 2026.
Which AWS AI certification should I take first?
Most people should start with AWS Certified AI Practitioner (AIF-C01). It costs $100, runs 90 minutes and needs no coding. If you lead AI work in a business role and never touch AWS services, the new AI Business Strategist (AIB-C01) is the alternative starting point.
Can I still take MLA-C01?
Not in English. The last day to take MLA-C01 in English was September 28, 2026, and the MLA-C02 beta started September 29, 2026 at $75. Japanese, Korean and Simplified Chinese versions stay available until MLA-C02 is generally available, which AWS's September 2026 blog dates to January 14, 2027.
What is ME1-C02?
ME1-C02 is the exam code AWS's certification page shows for the beta of the updated Machine Learning Engineer Associate exam. AWS's exam guide and blog call the same exam MLA-C02.
What replaced the AWS Machine Learning Specialty certification?
AWS retired MLS-C01 after March 31, 2026 and points candidates to AI Practitioner (AIF-C01), Machine Learning Engineer Associate, Data Engineer Associate and Generative AI Developer Professional (AIP-C01). For most former MLS candidates, the ML Engineer Associate or AIP-C01 is the closest fit.
How much do AWS AI certifications cost?
At list price, AIF-C01 is $100, the ML Engineer Associate is $150 ($75 for the MLA-C02 beta), AIP-C01 is $300, and AIB-C01 is $100 ($50 during its beta). Prices are in US dollars before tax.
Do AWS AI certifications expire?
Yes. Each AWS AI certification is valid for three years. You renew by passing the latest version of the exam with a 50% discount voucher, or by earning a higher certification: the ML Engineer Associate automatically recertifies AI Practitioner, and passing AIP-C01 renews both.
What is the hardest AWS AI certification?
The Generative AI Developer Professional (AIP-C01). It is AWS's professional-level AI exam, with 75 questions in 180 minutes and a 750 passing score, and AWS recommends two or more years building production applications plus a year of hands-on generative AI work.
