AWS AI Practitioner (AIF-C01): Exam Walkthrough & Mock Exam

Instructor: Mumshad Mannambeth

What you'll learn

Apply exam reasoning to AWS AI scenarios covering Amazon Bedrock, RAG, PII redaction, and the AI shared responsibility model.
Select appropriate performance metrics (Recall, Precision) and apply SageMaker Ground Truth for production ML lifecycle questions.
Evaluate and compare Foundation Models by cost, latency, and accuracy to make sound architectural decisions on AWS.
Determine when to use RAG vs. fine-tuning and implement IDP workflows with Amazon Textract in exam-style scenarios.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

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Assessments

7 assignments¹

AI Graded see disclaimer

Taught in English

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There are 3 modules in this course

The AWS Certified AI Practitioner (AIF-C01) exam doesn't reward memorisation. It tests your ability to apply AWS AI services to real-world scenarios — selecting the right tool, for the right reason, in the right context. This course is built around that distinction.

Spread across all three modules, a 40-question video walkthrough solves exam-style questions on screen, step by step. Each explanation focuses on the reasoning behind the correct answer — why the right option works and why the distractors don't — so you build the kind of transferable exam logic that holds up under time pressure. Three focused modules consolidate your knowledge across the key AIF-C01 domain areas. Module 1 covers Generative AI on AWS — Amazon Bedrock, RAG, PII redaction, and the shared responsibility model for AI security. Module 2 addresses the ML lifecycle in production — SageMaker Ground Truth for data labeling at scale, model monitoring and performance drift, explainability, governance, and selecting the right performance metrics (Recall vs. Precision) based on business impact. Module 3 sharpens architectural decision-making — when to use RAG vs. fine-tuning, how to evaluate Foundation Models by cost, latency, and accuracy, and how to implement Intelligent Document Processing (IDP) workflows using Amazon Textract. Two full-length mock exams, accessible via external links in Module 3, simulate the real certification experience and help you confirm your readiness before exam day. Who this is for: AWS practitioners with foundational cloud knowledge who are preparing to earn the AIF-C01 credential. Prior experience with AWS services is assumed. This is an exam preparation course, not an introductory AWS AI course.

This module introduces the core concepts of Generative AI and the architectural patterns used to deploy them on AWS. You will explore how Amazon Bedrock serves as a foundation for building secure applications, how to protect sensitive data with PII redaction, and how to mitigate common AI risks like hallucinations using Retrieval-Augmented Generation (RAG).

What's included

4 videos2 assignments

Moving beyond basic implementation, this module focuses on the "Care and Feeding" of machine learning models in a production environment. You will learn to navigate the ML lifecycle by labeling data at scale, monitoring for performance drift, and tuning hyperparameters like temperature to ensure consistent, high-quality model outputs.

What's included

2 videos2 assignments

The final module prepares you to make high-level architectural decisions by comparing different AI strategies and tools. You will learn the technical criteria for choosing between RAG and Fine-tuning, how to conduct side-by-side model evaluations on Bedrock, and how to automate complex data extraction from structured and unstructured documents.