AWS AI Practitioner study guide
AWS AI Practitioner · Work through your exam, one topic at a time.
The AWS Certified AI Practitioner is an entry-level credential from Amazon Web Services that validates foundational knowledge of artificial intelligence, machine learning, and generative AI on AWS. It is designed for people who work with AI-enabled tools and services rather than build models from scratch - product managers, business analysts, sales and marketing staff, developers new to AI, and anyone translating AI capabilities into business outcomes. The AWS AI Practitioner study guide has 5 sections and about 1,651 words.
01Fundamentals of AI and ML
AI is the broad goal of machines performing tasks that normally need human intelligence; machine learning (ML) is the technique of fitting models to data instead of hand-coding rules; deep learning is ML using multi-layer neural networks. Distinguish supervised learning (labelled data, e.g.
363 words, about 2 min02Fundamentals of Generative AI
A foundation model (FM) is trained on broad data at scale and adapted to many downstream tasks. Large language models are FMs trained on text to predict the next token.
330 words, about 2 min03Applications of Foundation Models
Amazon Bedrock provides managed access to foundation models from multiple providers through one API, with serverless scaling and no infrastructure management. Candidates should know Bedrock features: model choice, the Converse API for a consistent interface, Knowledge Bases for managed RAG, Agents for multi-step tasks that call APIs, Guardrails for filtering input and output, and provisioned throughput for predictable capacity.
316 words, about 2 min04Guidelines for Responsible AI
Responsible AI in AWS guidance centers on fairness, explainability, privacy, safety, controllability, verifiability, and governance. Fairness means avoiding bias against groups; explainability means understanding why a model produced an output; privacy means protecting personal data; safety means avoiding harmful output; controllability means keeping humans able to intervene; verifiability means being able to audit results; governance means documented oversight.
317 words, about 2 min05Security, Compliance, and Governance for AI Solutions
AWS operates on a shared responsibility model: AWS secures the cloud, customers secure what they put in it, including data, prompts, and model configuration. Use IAM for least-privilege access, roles rather than long-lived keys, and separate permissions for training, deployment, and data access.
325 words, about 2 min