The AWS Certified AI Practitioner is a foundational certification that validates knowledge of artificial intelligence, machine learning and generative AI concepts on AWS. It is designed for people who use or work alongside AI solutions — not only engineers who build them.
Who should take AI Practitioner?
- Business analysts, product managers and project managers working on AI initiatives
- Developers and cloud professionals new to AI
- Sales, marketing and consulting professionals who discuss AI with clients
- Anyone starting a path toward ML engineering on AWS
Exam overview
AI Practitioner is a foundational-level AWS exam. Like other AWS certifications, it is valid for three years.
Exam details such as price, length and question count change periodically — always confirm current information on the official certification page before you book.
Exam domains
- Fundamentals of AI and ML — AI vs. ML vs. deep learning, types of learning and the ML lifecycle
- Fundamentals of generative AI — foundation models, tokens, embeddings, prompts and use cases
- Applications of foundation models — prompt engineering, retrieval-augmented generation, fine-tuning and evaluation
- Guidelines for responsible AI — bias, fairness, transparency and explainability
- Security, compliance and governance for AI — data protection, IAM and governance practices
Key AWS services to know
- Amazon Bedrock — access to foundation models, knowledge bases, agents and guardrails
- Amazon SageMaker AI — building, training and deploying ML models
- Amazon Q — AI assistants for business users and developers
- AI services such as Comprehend, Rekognition, Textract, Transcribe, Translate, Polly and Lex
- Security services including IAM, KMS, CloudTrail and Macie
A 3–4 week study plan
- Week 1: AI/ML fundamentals and the ML lifecycle
- Week 2: Generative AI concepts, prompt engineering and RAG
- Week 3: AWS AI services, Bedrock and SageMaker basics; responsible AI and security
- Week 4: Practice questions and review
Try a few hands-on experiments in the Bedrock console — prompting models or building a simple knowledge base — to make the concepts concrete.
How it fits your career
AI literacy is becoming expected across roles. This certification demonstrates that you understand AI capabilities, limitations and risks. For deeper technical paths, continue to associate-level ML credentials and read how to become a machine learning engineer and AI jobs. See the full AWS certification path.
Frequently asked questions
Do I need coding skills for AWS AI Practitioner?
No. It focuses on concepts, use cases and AWS services rather than coding.
AI Practitioner or Cloud Practitioner — which first?
If your focus is AI, start with AI Practitioner. If you need broad AWS knowledge, start with Cloud Practitioner. Many people take both.
Is AWS AI Practitioner worth it?
It is valuable for building AI literacy and showing employers you understand generative AI on AWS, especially in non-engineering or early-career roles.
Earned a new certification? Make sure recruiters’ software sees it.
Applicant tracking systems search for exact certification names and acronyms. HiReXL tailors your resume to each job’s keywords — including certifications — while keeping your format. HiReXL is built by 4As Consulting, a cloud and DevOps consulting firm. Looking for your next role? Submit your resume for open positions with PanAmerica Inc.
