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AWS AI Practitioner

AWS Certified AI Practitioner: Foundations

An independent study guide for the AIF-C01 exam blueprint: AI and ML fundamentals, generative AI, foundation model applications, responsible AI, and security and governance. Written from scratch against the April 2026 v1.1 guide, and not affiliated with, endorsed by or sponsored by Amazon Web Services. It reproduces no exam questions.

6 modules · 10 hr 17 min of reading

4 of 40 lessons are open to read without an account, and a free account opens the other 36. Creating one costs nothing: there is no paid plan, no tier and nothing to buy.

Start readingHow this is checked
lessons
40
flashcards
195
quiz questions
156
practice questions
550

Practice exam

A sitting is 65 questions in 1 hr 30 min, reported on the 100 to 1000 scale the programme publishes, with 700 to pass.

  • Drawn fresh from a pool of 550, allocated across the domains by the weights below
  • Worked through unseen questions first, so a second sitting is a different paper
  • Feedback held back until you submit, then every option explained and the score split by domain
Fundamentals of AI and ML
20 per cent of the paper
Fundamentals of Generative AI
24 per cent of the paper
Applications of Foundation Models
28 per cent of the paper
Guidelines for Responsible AI
14 per cent of the paper
Security, Compliance, and Governance for AI Solutions
14 per cent of the paper

The weights are the published blueprint's. The questions are not: all 550 were written here from the published objectives, and none of them is a real exam question.

Course outline

  1. Module 1

    Open to read

    Orientation: what AIF-C01 measures

    What the AWS Certified AI Practitioner exam is, the five domains and their weights, the service surface it expects you to recognise, and how the April 2026 revision changed it. Read this first: it also sets out what this guide is and is not.

    4 lessons · 55 min

    Before you start

    • What the AIF-C01 exam measures
    • The service surface, as a map
    • How to prepare for a moving target
    • What this guide is sure about

  2. Module 2

    Free account

    Domain 1: Fundamentals of AI and ML

    20% of the exam. What AI, machine learning and deep learning actually are, the kinds of learning and inference, how to tell a good AI use case from a bad one, and the machine learning lifecycle.

    7 lessons · 1 hr 46 min

    Core concepts

    • AI, machine learning and deep learning
    • Types of learning
    • Data types and inference modes

    Use cases and the lifecycle

    • Spotting a good AI use case
    • Choosing a machine learning technique
    • AWS managed AI services
    • The machine learning lifecycle and MLOps

  3. Module 3

    Free account

    Domain 2: Fundamentals of generative AI

    24% of the exam. Tokens, embeddings and vectors, how foundation models work, the model lifecycle, token pricing and context engineering, agentic AI and MCP, and the AWS generative AI stack.

    9 lessons · 2 hr 17 min

    Generative AI concepts

    • Tokens, embeddings and vectors
    • How foundation models work
    • Generative AI use cases
    • The foundation model lifecycle
    • Token pricing and context engineering

    Capabilities and the AWS stack

    • Agentic AI, MCP and orchestration
    • Advantages and limitations
    • Selecting a model and measuring value
    • The AWS generative AI stack

  4. Module 4

    Free account

    Domain 3: Applications of foundation models

    The largest domain at 28%. Choosing and configuring a model, retrieval-augmented generation and vector stores, customisation and its costs, prompt engineering and its risks, fine-tuning, and evaluating both the model and the business outcome.

    10 lessons · 2 hr 39 min

    Designing an application

    • Choosing a foundation model
    • Inference parameters and what they actually change
    • Retrieval-augmented generation
    • Vector stores on AWS
    • Customisation approaches and what they cost

    Prompting, tuning and evaluation

    • Prompt engineering techniques
    • Prompt risks and prompt management
    • Training and fine-tuning foundation models
    • Evaluating model performance
    • Evaluating applications and business fit

  5. Module 5

    Free account

    Domain 4: Guidelines for responsible AI

    14% of the exam. What responsible AI means in practice, bias and variance, datasets and their effects, guardrails and bias detection, legal and reputational risk, and transparent, explainable models.

    5 lessons · 1 hr 17 min

    Building responsibly

    • What responsible AI means
    • Bias, variance and the datasets behind them
    • Guardrails and bias detection on AWS
    • Legal and reputational risk

    Transparency and explainability

    • Transparent and explainable models

  6. Module 6

    Free account

    Domain 5: Security, compliance and governance

    14% of the exam. Securing AI systems on AWS, data lineage and secure data engineering, the threats specific to AI systems, grounding against hallucination, and the governance, compliance and audit obligations that follow.

    5 lessons · 1 hr 23 min

    Securing the system

    • Securing an AI workload on AWS
    • Data lineage and secure data engineering
    • Threats to AI systems
    • Grounding and hallucination detection

    Governance and compliance

    • Governance, compliance and audit

Where this course comes from

Independent study guide. Structure follows the publicly published AIF-C01 exam guide (v1.1, 30 April 2026); all explanations, examples and practice questions are our own.

Start with the orientation module

It reads with no account at all, and it sets out what the exam measures, how to prepare for it, and what this guide is and is not sure about.

Start readingAll courses

4 of 40 lessons are open to read without an account, and a free account opens the other 36. There is no paid plan, no tier and nothing to buy.