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Tom Taulli AWS Certif ied AI Practitioner (AIF-C01) Study Guide In-Depth Exam Prep and Practice

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ISBN: 979-8-341-62233-3 US $59.99 CAN $74.99 CLOUD COMPUTING Tom Taulli is a consultant and author who specializes in AI and software development. He has written multiple books and taught courses for UCLA, Pluralsight, and O’Reilly on topics like Python, machine learning, and natural language processing. AI is transforming industries, and cloud-based AI expertise is in high demand. This study guide is your essential resource for mastering foundational AI concepts and AWS tools while preparing for the AIF-C01 certification exam. Author Tom Taulli breaks down complex topics into practical, easy-to-understand lessons that will enhance the test-readiness of IT professionals, developers, or data analysts looking to expand into AI. Covering key areas like machine learning, natural language processing, computer vision, and generative AI, this guide also provides hands-on experience with AWS tools such as SageMaker, Bedrock, Rekognition, and Comprehend. With real-world examples, ethical considerations, and exam-focused strategies, it will give you the confidence to both pass the exam and apply AI concepts in your career. • Understand core AI principles and their applications in AWS • Learn how to use AWS’s AI tools for real-world business solutions • Grasp key exam strategies with practice questions and expert insights • Apply AI techniques confidently in cloud environments • Achieve certification and enhance your career in AI and cloud computing AWS Certified AI Practitioner (AIF-C01) Study Guide “Tom masterfully simplifies the landscape of AI on AWS. This book is a practical, well-structured resource for preparing for the AWS AI Practitioner exam, especially for data professionals looking to ground their cloud knowledge in real-world use cases.” Pramesh Anuragi Data scientist

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Tom Taulli AWS Certified AI Practitioner (AIF-C01) Study Guide In-Depth Exam Prep and Practice

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979-8-341-62233-3 [LSI] AWS Certified AI Practitioner (AIF-C01) Study Guide by Tom Taulli Copyright © 2025 Tom Taulli. All rights reserved. Published by O’Reilly Media, Inc., 141 Stony Circle, Suite 195, Santa Rosa, CA 95401. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com). For more information, contact our corporate/institutional sales department: 800-998-9938 or corporate@oreilly.com. Acquisitions Editor: Megan Laddusaw Development Editor: Sara Hunter Production Editor: Beth Kelly Copyeditor: nSight, Inc. Proofreader: Kim Wimpsett Indexer: Sue Klefstad Cover Designer: Karen Montgomery Cover Illustrator: Monica Kamsvaag Interior Designer: David Futato Interior Illustrator: Kate Dullea August 2025: First Edition Revision History for the First Edition 2025-08-14: First Release See http://oreilly.com/catalog/errata.csp?isbn=9798341622333 for release details. The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. AWS Certified AI Practitioner (AIF- C01) Study Guide, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. The views expressed in this work are those of the author and do not represent the publisher’s views. While the publisher and the author have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the author disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights.

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Table of Contents Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi 1. Why Certify? An Introduction to the AWS AI Practitioner Exam. . . . . . . . . . . . . . . . . . . . . 1 Why Should You Take This Exam? 2 Recognition 2 The Growth of AI 2 AWS Remains Dominant 2 Boosting Your Salary, Productivity, and Career with AI Skills 3 Improving Economic Growth and Business Operations 3 Topics Covered in the Exam 4 Exam Details 4 Other Certifications 6 AWS Resources 7 Other Important Information 8 Updates 8 Conclusion 8 2. AWS Fundamentals for the AI Practitioner. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Cloud Computing 10 Cloud Models 11 Public Cloud 11 Private Cloud 12 Hybrid Cloud 12 Cloud Service Types 13 Infrastructure as a Service 14 Platform as a Service 14 iii

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Software as a Service 16 AWS Regions, Availability Zones, and Local Zones 17 Region 17 Availability Zones 18 Local Zones 18 Pricing Models 19 Core AWS Services: An eCommerce Example 20 Data Ingestion 20 Data Processing 21 Storage and Databases 21 Analytics and Recommendations 22 Content Delivery 23 Monitoring and Logging 23 Shared Responsibility Model 24 AWS IAM 25 Setting Up AWS 26 Conclusion 28 Quiz 28 3. AI and Machine Learning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Understanding AI 31 Machine Learning 33 Amazon SageMaker 34 The ML Lifecycle 35 Business Goal Identification 36 ML Problem Framing 36 Data Processing 37 Model Development 39 Model Deployment 50 Monitoring 51 MLOps 52 AWS Development Tools 53 SageMaker Notebook Instances 54 SageMaker Studio Classic 55 AWS ML Services 56 Conclusion 59 Quiz 59 4. Understanding Generative AI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Neural Networks and Deep Learning 61 Generative AI Models 62 Generative Adversarial Network 62 iv | Table of Contents

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Variational Autoencoder 64 Transformer Model 65 Diffusion Model 68 Foundation Models 70 Data Selection 71 Pretraining 71 Optimization 72 Evaluation 76 Deployment 83 Capabilities of Generative AI 83 Drawbacks of Generative AI 84 Hallucinations 85 Nondeterminism 85 Interpretability 86 Data Security and Privacy 86 Social and Branding Risks 87 Limited Context Windows 87 Recency 88 Costs 88 Data Challenge 90 Evolution of FMs 90 AGI 91 Conclusion 93 Quiz 93 5. Real-World AI Applications with AWS Tools. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Computer Vision 96 Amazon Rekognition 96 Natural Language Processing 98 Amazon Comprehend 99 Amazon Kendra 100 Amazon Lex 101 Amazon Polly 102 Amazon Transcribe 103 Amazon Translate 104 Intelligent Document Processing 105 Fraud Detection 107 When to Use AI? 107 Conclusion 108 Quiz 108 Table of Contents | v

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6. Building with Amazon Bedrock and Amazon Q. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Getting Started with Amazon Bedrock 112 Chat/Text Playground 115 Interacting with the FM 120 Image/Video Playground 121 Choosing an FM 124 License Types 125 FM Response Analysis 126 Measuring Success: Business Goals and Metrics 128 User Satisfaction 128 Average Revenue per User 128 Conversion Rate 129 Efficiency 130 Model Customization 130 Distillation 130 Fine-Tuning 131 Continued Pretraining 132 Agents in Amazon Bedrock 132 Multiagent Collaboration 134 Pricing 135 Amazon Q 135 Amazon Q Business 136 Amazon Q Developer 136 Benefits of Bedrock and Amazon Q 137 Conclusion 137 Quiz 138 7. A Guide to Prompt Engineering. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 The Anatomy of a Prompt 141 Instruction 142 Context 143 Input Data 143 Output Indicator 144 Best Practices for Prompting 146 Be Clear 146 Avoid Leading Questions 147 Use Analogies or Comparisons 148 Ask for Alternatives 148 Use Prompt Templates 149 Prompting Techniques 150 Zero-Shot Prompting 150 Few-Shot Prompting 150 vi | Table of Contents

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Chain-of-Thought Prompting (CoT) 151 Security Issues 152 Model Poisoning 152 Hijacking and Prompt Injection 153 Exposure 153 Prompt Leaking 154 Jailbreaking 154 Conclusion 154 Quiz 155 8. A Framework for Responsible AI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Risks of Generative AI 157 Toxicity 158 Intellectual Property 158 Plagiarism and Cheating 159 Disruption of the Nature of Work 160 Accuracy 160 Elements of Responsible AI 161 Fairness 162 Explainability 162 Privacy and Security 163 Transparency 163 Veracity and Robustness 163 Governance 164 Safety 164 Controllability 165 The Benefits of Responsible AI 165 Amazon Tools for Responsible AI 166 Amazon Bedrock 166 SageMaker Clarify and Experiments 167 Amazon Augmented AI (Amazon A21) 167 SageMaker Model Monitor 168 Going Further with Responsible AI 168 Sustainability and Environmental Considerations 169 Data Preparation 170 Interpretability Versus Explainability 170 Human-Centered Design 171 RLHF 172 Conclusion 173 Quiz 173 Table of Contents | vii

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9. Security, Compliance, and Governance for AI Solutions. . . . . . . . . . . . . . . . . . . . . . . . . . 175 Overview of Security, Compliance, and Governance 175 Security 176 Compliance 183 Governance 187 Conclusion 195 Quiz 195 10. Strategies and Techniques for Successfully Taking the AWS Certified AI Practitioner (AIF-C01) Exam. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Tips When Taking the Exam 197 Manage Your Time 198 Read Questions Carefully 198 Use the Process of Elimination 198 Stay Calm and Double-Check Your Answers 198 Crash Course: What to Know Before Exam Day 199 Fundamentals of AI and ML 199 Fundamentals of Generative AI 200 Applications of FMs 201 Guidelines for Responsible AI 202 Security, Compliance, and Governance for AI Solutions 202 Conclusion 203 A. Practice Exam. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 B. Answer Key. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Glossary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 viii | Table of Contents

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Foreword Artificial intelligence (AI) is one of the most transformative technologies of our life‐ time. For more than 25 years, Amazon has invested in the development of AI and machine learning (ML) because we believe these technologies have the power to transform the lives of our customers and communities. With the rise of generative AI, we’re seeing more organizations adopt AI services to drive innovation and unlock extraordinary capabilities. But while AI makes innova‐ tion possible, it’s people who make it happen. This human element is precisely why organizations are actively seeking AI talent. Our research shows 92% of organizations have plans to hire people with AI skills to help them drive AI innovations. While this is welcome news, there’s currently a global AI talent shortage. Three out of four employers consider hiring AI-skilled talent a priority but can’t find the AI talent they need. That’s why in 2023, we made a commitment to provide free AI skills training for two million people worldwide by 2025 as part of Amazon’s AI Ready initiative. Through this commitment, learners are applying their knowledge to their jobs to help them become more productive and creative, showcasing their skills to prospective employ‐ ers to help them become more competitive candidates, or pursuing further training to build a career in AI. We reached our AI Ready goal a year ahead of schedule, but it’s just the beginning. We’ll continue helping more people upskill in AI because AI skills have become essential to the modern workforce. Organizations and people who invest in AI skills training are better equipped to keep pace with the rapid advancements in this area and thrive in an era of unprecedented technological change. I’m thrilled you’re embarking on the AI upskilling journey by pursuing the AWS Cer‐ tified AI Practitioner. Tom’s book is an excellent resource to help you prepare for the exam in addition to the exam prep that AWS offers. It’s a thorough guide that covers the basics of AWS, AWS AI, and ML services and tools; responsible AI; strategies to help pass the exam; and so much more. ix

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Throughout my career, I’ve acquired new skills at each stage to deliver value to the organizations I’ve been fortunate to work with. I’m a firm believer that curiosity and a commitment to lifelong learning will also be the key to advancing your career. Whether this is your first certification or one of many in your toolbox, you’re demon‐ strating these values that will prepare you for an AI-driven future. Your investment in AI upskilling will not only empower you to build an enduring and meaningful career for yourself but also unlock exciting innovations that will benefit future generations. — Michelle Vaz Managing Director, Amazon Web Services (AWS) Training and Certification x | Foreword

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Preface AI isn’t some distant, futuristic concept anymore. It’s here. It’s real. And it’s changing how we work across almost every field you can name: software, marketing, health‐ care, finance, education, and beyond. What used to be the domain of data scientists and PhDs has gone mainstream. Today, if you understand how to use AI effectively, you’ve got an edge. That’s why learning AI isn’t just a nice-to-have skill—it’s something you need. And sure, there are plenty of ways to get started: online courses, tutorials, videos, books. But if you’re looking to stand out and show employers you’re serious, having a certifi‐ cation can make a real difference. It’s more than just a piece of paper. It’s proof that you know your stuff and can apply it where it matters. If you’re trying to figure out which certification is worth your time, the AWS Certified AI Practitioner is a strong bet. After all, AWS is the backbone of everything from tiny startups to tech giants. Getting certified here means you’re not only learning AI— you’re learning how to build and scale smart applications using tools that power some of the most innovative companies. The exam itself covers all the essentials: machine learning (ML), deep learning, natu‐ ral language processing (NLP), computer vision, generative AI, and responsible AI. But it doesn’t stop at theory. It ties everything back to the AWS ecosystem. You’ll get hands-on with these Amazon services: SageMaker, Comprehend, Rekognition, Tran‐ scribe, and Bedrock. Whether you’re looking to pivot into a new role, level up in your current one, or lead AI projects with confidence, this certification gives you a solid foundation. And this book is here to help you get there. Inside, you’ll find practical advice, easy-to- understand explanations, and plenty of guidance that’s directly aligned with the exam. If you’ve been thinking about diving into AI, now is the time. The tools are accessible, the demand is growing, and AWS gives you a powerful platform to build from. Use xi

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this book as your launchpad. Let’s get started—you’ve got a lot of exciting ground to cover. What’s Covered Here’s a brief look at each chapter: Chapter 1, “Why Certify? An Introduction to the AWS AI Practitioner Exam”, pro‐ vides an overview of the certification. This chapter details the reasons for taking the exam, including career and salary boosts, and outlines its intended audience. It also breaks down the exam’s topics, format, cost, and other relevant certifications to consider. Chapter 2, “AWS Fundamentals for the AI Practitioner”, describes the basics of the AWS platform and cloud computing. The chapter explores the different cloud models (public, private, hybrid) and service types (IaaS, PaaS, SaaS). It also covers the AWS global infrastructure, including regions and availability zones, and introduces core services like Amazon EC2, Amazon S3, and the shared responsibility model for security. Chapter 3, “AI and Machine Learning”, looks at key AI and ML concepts. It describes the different types of ML, including supervised, unsupervised, and reinforcement learning. The chapter details the complete ML lifecycle, from identifying business goals and data processing to model deployment and monitoring. It also introduces Amazon SageMaker as the primary service for building, training, and deploying ML models on AWS. Chapter 4, “Understanding Generative AI”, explores the core technologies behind generative AI, such as neural networks and deep learning. It details various generative models, including GANs, VAEs, diffusion models, and the transformer model archi‐ tecture. The chapter also covers foundation models (FMs), their development lifecy‐ cle, optimization techniques like fine-tuning and retrieval-augmented generation (RAG), and key evaluation metrics. Chapter 5, “Real-World AI Applications with AWS Tools”, highlights practical, real- world use cases for AI and the AWS tools that power them. It covers computer vision using Amazon Rekognition, NLP with services like Amazon Comprehend and Ama‐ zon Lex, and intelligent document processing (IDP) with Amazon Textract. The chapter also discusses using AI for fraud detection and provides guidance on when it is appropriate to use AI to solve business problems. Chapter 6, “Building with Amazon Bedrock and Amazon Q”, provides a deep dive into AWS’s primary services for building and using generative AI. It details Amazon Bedrock, a platform for accessing and customizing FMs using features like xii | Preface

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playgrounds, agents, and knowledge bases. The chapter also introduces Amazon Q, an AI-powered assistant for both business and developer use cases. Chapter 7, “A Guide to Prompt Engineering”, provides guidance on how to craft effective prompts to guide FM responses. The chapter breaks down prompts into four key components: instruction, context, input data, and output indicator. It covers best practices and techniques such as zero-shot, few-shot, and chain-of-thought prompt‐ ing, while also addressing security risks like prompt injection and jailbreaking. Chapter 8, “A Framework for Responsible AI”, focuses on the principles required to develop and deploy AI systems in a safe, trustworthy, and ethical manner. It explores key risks like toxicity, intellectual property infringement, and bias, and details the core tenets of responsible AI, including fairness, explainability, transparency, and safety. The chapter also highlights AWS tools that support these principles, such as Amazon SageMaker Clarify and guardrails for Amazon Bedrock. Chapter 9, “Security, Compliance, and Governance for AI Solutions”, explains secu‐ rity strategy and the Generative AI Security Scoping Matrix. The chapter covers key compliance standards like HIPAA and GDPR and explores data governance concepts, including data lineage and retention policies, along with the AWS tools that support them. Chapter 10, “Strategies and Techniques for Successfully Taking the AWS Certified AI Practitioner (AIF-C01) Exam”, summarizes the most critical topics from the book to guide final study sessions. Conventions Used in This Book The following typographical conventions are used in this book: Italic Indicates new terms, URLs, email addresses, filenames, and file extensions. This element signifies a general note. O’Reilly Online Learning For more than 40 years, O’Reilly Media has provided technol‐ ogy and business training, knowledge, and insight to help companies succeed. Preface | xiii

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Our unique network of experts and innovators share their knowledge and expertise through books, articles, and our online learning platform. O’Reilly’s online learning platform gives you on-demand access to live training courses, in-depth learning paths, interactive coding environments, and a vast collection of text and video from O’Reilly and 200+ other publishers. For more information, visit https://oreilly.com. How to Contact Us Please address comments and questions concerning this book to the publisher: O’Reilly Media, Inc. 141 Stony Circle, Suite 195 Santa Rosa, CA 95401 800-889-8969 (in the United States or Canada) 707-827-7019 (international or local) 707-829-0104 (fax) support@oreilly.com https://oreilly.com/about/contact.html We have a web page for this book, where we list errata and any additional informa‐ tion. You can access this page at https://oreil.ly/aws-certified-ai-practitioner. For news and information about our books and courses, visit https://oreilly.com. Find us on LinkedIn: https://linkedin.com/company/oreilly-media. Watch us on YouTube: https://youtube.com/oreillymedia. Acknowledgments I want to thank the awesome team at O’Reilly. They include Megan Laddusaw and Sara Hunter. I also had the benefit of outstanding tech reviewers. They are Pramesh Anuragi, Amith Bhanudas, and Sofia Leiby. xiv | Preface

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CHAPTER 1 Why Certify? An Introduction to the AWS AI Practitioner Exam The Amazon Web Services (AWS) Certified AI Practitioner certification—which has the exam code of AIF-C01—is focused at the entry level for artificial intelligence (AI), machine learning (ML), and generative AI. The exam addresses numerous AWS tools. According to Jenni Troutman, who is the director of Products and Services at AWS Training and Certification: The AWS Certified AI Practitioner exam is a foundational AI certification that is designed for people from a variety of backgrounds and experiences to show their understanding of AI and generative AI concepts, their ability to recognize opportuni‐ ties that benefit from AI, and their knowledge on using AI tools responsibly. If you already know about these topics, this will certainly help with the exam. But it is not a requirement. This book will provide what you need to know, breaking down the concepts that are covered in the exam. There are also sample questions at the end of each chapter, as well as a practice exam. In this chapter, we’ll look at the following: • The reasons to take the exam • The audience for it • Topics covered in the exam • Other certifications to consider 1

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Why Should You Take This Exam? Getting the AWS Certified AI Practitioner certification can be a boost to your career. This is particularly important in the AI industry, which is growing at a rapid pace. Let’s take a closer look. Recognition The certification makes a statement. It shows employers that you understand the basics of AI, along with AWS, which is Amazon’s massive cloud platform. You can also highlight the certification among your network, such as on LinkedIn, with a digi‐ tal badge for your profile. Even if you do not plan to pursue an AI role, the certification will still be valuable. After all, when it comes to many jobs nowadays—whether in sales, marketing, legal, and so on—there is usually a need to understand AI. The Growth of AI Gartner forecasts that spending on AI software will hit $297.9 billion by 2027, repre‐ senting an annual growth rate of 19.1%. Businesses have been investing heavily in AI so as to bolster efficiency and productivity. But this powerful technology can also be a driver for growth by unlocking insights from corporate data. Of course, this means businesses will need AI-savvy employees. According to a study commissioned by AWS, over 90% of employers expect to adopt AI-related solutions within the next five years. Some of the companies that have been training employees for the AWS Certified AI Practitioner and AWS Certified Machine Learning Engineer (associate certifications) include Capgemini, Cognizant, Compass, Deloitte, DXC Technology, EPAM, Kyndryl, N-iX, SoftwareOne, Tata Consultancy Services, and Wipro. AWS Remains Dominant AWS is the dominant player in the global cloud infrastructure market. For the first quarter of 2024, its market share came to 31%. Microsoft’s share is at 25%, and Goo‐ gle Cloud is at 10%. In the third quarter of 2024, AWS brought in $27.5 billion in revenue. This repre‐ sented a 19% increase from the same period a year ago. At the heart of the growth has been AWS’s AI segment. For 2024, the revenue surged at a triple-digit pace. 2 | Chapter 1: Why Certify? An Introduction to the AWS AI Practitioner Exam

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Boosting Your Salary, Productivity, and Career with AI Skills “Having AI skills can improve productivity,” said Troutman. “In fact, 88% of workers expect to use AI in their daily work by 2028 to automate repetitive tasks and drive creativity. In our own research, we also found that employees who have AWS certifi‐ cations have improved their interactions with their technical colleagues and customers.” In light of these benefits, there has been strong gains in compensation for those with AI skills. Consider a November 2023 AWS study. It shows that their salaries are gen‐ erally 43% higher for those in sales and marketing roles, 42% higher for finance roles, 41% higher for business operations roles, and 47% higher for IT specialists. Then what about those who have AI roles? Here’s a look at the average compensation levels in the United States, according to data from Coursera: Data analyst This person can earn a starting salary from $60,000 to $90,000. This depends on a person’s background and location. For example, a data analyst living in San Francisco earns an average of $95,000. AI developer An AI developer or ML engineer builds, deploys, and monitors AI projects and models. They understand languages like Python and various frameworks, such as TensorFlow, PyTorch, or scikit-learn. An AI developer earns anywhere from $85,000 to $120,000 per year. Project manager A project manager can earn from $90,000 to $130,000 annually. Their salary depends on their skill sets and the complexity of the projects they manage. Sales specialist for AI solutions The salary is typically between $70,000 and $110,000 per year, but the compensa‐ tion can be much higher because of commissions. Improving Economic Growth and Business Operations A McKinsey report estimates that generative AI systems will add $2.6 trillion to $4.4 trillion to the annual GDP for the globe because of expected improvements in pro‐ ductivity and efficiency. The industries that are likely to see the biggest impact include banking, high tech, and life sciences. Then there is research from Goldman Sachs, which predicts that generative AI could increase global GDP by $7 trillion and productivity growth could be increased by 1.5% for the next decade. One of the firm’s software analysts, Kash Rangan, noted that Why Should You Take This Exam? | 3

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“generative AI can streamline business workflows, automate routine tasks, and give rise to a new generation of business applications.” In other words, businesses will need to adopt and use AI systems effectively. It could be essential for them. Topics Covered in the Exam The AWS exam guide provides the topics you’ll be tested on and the percentage of questions for each section (see Table 1-1). Table 1-1. Topics on the AIF-C01 exam Domain Key objectives 1. Fundamentals of AI and ML (20%) Explain basic AI concepts and terminologies. Identify practical use cases for AI. Describe the machine learning development lifecycle. 2. Fundamentals of Generative AI (24%) Explain the basic concepts of generative AI. Understand the capabilities and limitations of generative AI for solving business problems. Describe AWS infrastructure and technologies for building generative AI applications. 3. Applications of Foundation Models (28%) Describe design considerations for applications that use FMs. Choose effective prompt engineering techniques. Describe the training and fine-tuning process for FMs. Describe methods to evaluate FM performance. 4. Guidelines for Responsible AI (14%) Explain the development of responsible AI systems. Recognize the importance of transparent and explainable models. 5. Security, Compliance, and Governance for AI Solutions (14%) Explain methods to secure AI systems. Recognize governance and compliance regulations for AI systems. Best practices: secure data engineering, transparency, and training. In this table, notice that more than half of the exam focuses on generative AI (domains 2 and 3). But this should not be a surprise. This technology is often the main focus for AI projects and implementations. Exam Details The exam contains 65 questions, of which 50 are scored and 15 are unscored (these are not disclosed). The unscored questions don’t impact your final score because they are experimental. They are a way to help AWS evaluate these questions for future exams. Regardless, there’s no penalty for guessing. If you’re unsure about an answer, take your best shot. 4 | Chapter 1: Why Certify? An Introduction to the AWS AI Practitioner Exam

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