Course and practice questions
AI Practitioner course
AI Practitioner (AIF-C01): 5 modules, 15 lessons and 5 quizzes. This exam is multiple choice, so the practice is the course and original questions. The lab runtime is kubeadm clusters only, and this page does not include an AWS account.
What's included
A course and practice questions
5 modules, 15 lessons and 5 quizzes (40 original questions). About 2 h 9 min of reading. The lab runtime is kubeadm clusters only, so this page does not include an AWS account.
5 modules
15 lessons mapped to the domains in the public exam guide.
5 quizzes
40 original practice questions, with an explanation for every answer. They are not exam items.
90-minute exam
The length published for this exam. This page does not offer a timed mock.
Exam domains
Domains from the public guide
The domain weights below sum to 100. The official page is the source of truth: AI Practitioner exam page.
Applications of Foundation Models
28%of the exam
4 competencies
- Describe design considerations for applications that use foundation models
- Choose effective prompt engineering techniques
- Describe the training and fine-tuning process for foundation models
- Describe methods to evaluate foundation model performance
Fundamentals of GenAI
24%of the exam
3 competencies
- Explain the basic concepts of generative AI
- Understand the capabilities and limitations of GenAI for solving business problems
- Describe AWS infrastructure and technologies for building GenAI applications
Fundamentals of AI and ML
20%of the exam
3 competencies
- Explain basic AI concepts and terminologies
- Identify practical use cases for AI
- Describe the AI/ML development lifecycle
Guidelines for Responsible AI
14%of the exam
2 competencies
- Explain the development of AI systems that are responsible
- Recognize the importance of transparent and explainable models
Security, Compliance, and Governance for AI Solutions
14%of the exam
2 competencies
- Explain methods to secure AI systems
- Recognize governance and compliance regulations for AI systems
Curriculum
5 modules, 15 lessons, 5 quizzes
Lesson titles from the course. The questions stay in the quizzes, and the answers are not published here.
01Fundamentals of AI and ML
The vocabulary of AI and machine learning, when a use case is real, and the lifecycle from a business question to a monitored model. Domain: Fundamentals of AI and ML.
- lessonAI, machine learning, and the words around them9 min
- lessonChoosing a use case, and the AWS service that fits it9 min
- lessonThe AI and ML development lifecycle8 min
02Fundamentals of generative AI
Tokens, embeddings, foundation models, what generation can and cannot do, and the AWS services this exam uses to build on them. Domain: Fundamentals of GenAI.
- lessonTokens, embeddings, and foundation models9 min
- lessonWhat generative AI can and cannot do8 min
- lessonAWS services for generative AI applications9 min
03Applications of foundation models
How you design around a foundation model, how you prompt it, and how you adapt and evaluate it without treating a benchmark as a launch decision. Domain: Applications of Foundation Models.
- lessonDesigning an application on a foundation model10 min
- lessonPrompt engineering that holds up9 min
- lessonFine-tuning and evaluating foundation models9 min
04Responsible AI
Fairness, safety, oversight, and the difference between a model you can explain and a model you can only watch. Domain: Guidelines for Responsible AI.
- lessonFeatures of a responsible system8 min
- lessonHarm, oversight, and the data you train on8 min
- lessonTransparency and explainability8 min
05Security, compliance, and governance
IAM, encryption, private connectivity, prompt injection, grounding, and the AWS services that give an auditor evidence. Domain: Security, Compliance, and Governance for AI Solutions.
- lessonSecuring an AI system9 min
- lessonPrompt injection, leakage, and grounding8 min
- lessonGovernance, compliance, and the services that record them8 min
Read the AI Practitioner course
Sign up free to read the 15 lessons and take the 5 quizzes. The lab runtime is kubeadm clusters only, so this course does not include an AWS account.