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AWS AI Practitioner Exam Guide

A comprehensive 4-week study plan to help you prepare for the AWS AI Practitioner certification exam.

Exam Information

90 minutes

Duration

65 questions

Questions

700/1000

Passing Score

$100 USD

Exam Cost

Recommended Study Plan

Week 1

AI/ML Fundamentals

Fundamentals of AI and ML (20%)

8-10 hours

Basic AI/ML concepts and terminology
Types of machine learning (supervised, unsupervised, reinforcement)
Deep learning and neural networks basics
AI/ML pipeline and lifecycle

Recommended Resources:

AWS Documentation

Machine Learning Basics

Week 2

Fundamentals of Generative AI

Fundamentals of Generative AI (24%)

10-12 hours

Large Language Models (LLMs)
Foundation models and transformers
Prompt engineering techniques
Generative AI use cases and applications

Recommended Resources:

Amazon Bedrock Docs

AWS Tutorials

Week 3

AWS AI/ML Services

Applications of Foundation Models (28%)

12-14 hours

Amazon SageMaker overview
Amazon Bedrock and foundation models
Amazon Rekognition, Textract, Comprehend
Amazon Polly, Transcribe, and Translate

Recommended Resources:

AWS Console

Hands-on Labs

Week 4

Responsible AI & Review

Guidelines for Responsible AI (28%)

10-12 hours

AI ethics and bias mitigation
Responsible AI practices
Security and compliance for AI
Review and practice exams

Recommended Resources:

AWS Well-Architected ML

Practice Exams

Exam Tips & Strategies

Understand Concepts

Focus on understanding AI/ML concepts rather than memorization. Know when to use which AWS AI service.

Generative AI Focus

Generative AI makes up a significant portion of the exam. Understand LLMs, foundation models, and prompt engineering.

Try Bedrock

Use Amazon Bedrock in the AWS console to understand how foundation models work and how to interact with them.

Responsible AI

Don't skip the responsible AI section. Understanding bias, ethics, and security is crucial for the exam.

Key Topics to Master

Machine learning types and algorithms

Neural networks and deep learning basics

Large Language Models (LLMs)

Foundation models and fine-tuning

Prompt engineering techniques

Amazon Bedrock and model selection

Amazon SageMaker capabilities

Amazon Rekognition for image/video

Amazon Comprehend for NLP

Amazon Textract for document processing

AI/ML bias and fairness

Model evaluation metrics

Responsible AI principles

Security for AI workloads

Cost optimization for AI services

For the most up-to-date exam information, visit the official exam guide.

View Official Exam Guide

Back to AIF-C01

AWS AI Practitioner Exam Guide

A comprehensive 4-week study plan to help you prepare for the AWS AI Practitioner certification exam.

Exam Information

90 minutes

Duration

65 questions

Questions

700/1000

Passing Score

$100 USD

Exam Cost

Recommended Study Plan

Week 1

AI/ML Fundamentals

Fundamentals of AI and ML (20%)

8-10 hours

Basic AI/ML concepts and terminology
Types of machine learning (supervised, unsupervised, reinforcement)
Deep learning and neural networks basics
AI/ML pipeline and lifecycle

Recommended Resources:

AWS Documentation

Machine Learning Basics

Week 2

Fundamentals of Generative AI

Fundamentals of Generative AI (24%)

10-12 hours

Large Language Models (LLMs)
Foundation models and transformers
Prompt engineering techniques
Generative AI use cases and applications

Recommended Resources:

Amazon Bedrock Docs

AWS Tutorials

Week 3

AWS AI/ML Services

Applications of Foundation Models (28%)

12-14 hours

Amazon SageMaker overview
Amazon Bedrock and foundation models
Amazon Rekognition, Textract, Comprehend
Amazon Polly, Transcribe, and Translate

Recommended Resources:

AWS Console

Hands-on Labs

Week 4

Responsible AI & Review

Guidelines for Responsible AI (28%)

10-12 hours

AI ethics and bias mitigation
Responsible AI practices
Security and compliance for AI
Review and practice exams

Recommended Resources:

AWS Well-Architected ML

Practice Exams

Exam Tips & Strategies

Understand Concepts

Focus on understanding AI/ML concepts rather than memorization. Know when to use which AWS AI service.

Generative AI Focus

Generative AI makes up a significant portion of the exam. Understand LLMs, foundation models, and prompt engineering.

Try Bedrock

Use Amazon Bedrock in the AWS console to understand how foundation models work and how to interact with them.

Responsible AI

Don't skip the responsible AI section. Understanding bias, ethics, and security is crucial for the exam.

Key Topics to Master

Machine learning types and algorithms

Neural networks and deep learning basics

Large Language Models (LLMs)

Foundation models and fine-tuning

Prompt engineering techniques

Amazon Bedrock and model selection

Amazon SageMaker capabilities

Amazon Rekognition for image/video

Amazon Comprehend for NLP

Amazon Textract for document processing

AI/ML bias and fairness

Model evaluation metrics

Responsible AI principles

Security for AI workloads

Cost optimization for AI services

For the most up-to-date exam information, visit the official exam guide.

View Official Exam Guide