Overview & Exam Structure
Hello! 👋 Lucy here. Welcome to my complete set of study notes for the AWS AI Practitioner Certification.
In these notes, you'll find a detailed breakdown of each Domain and Task Statement covered in the exam guide. I have also revised the notes after my exam, to make sure all the key concepts and services are covered.
What's included:
✅ Concise, easy-to-read Study Notes for each task statement of the exam.
✅ PDF Summary of all important concepts and services.
✅ Mini Practice Test to assess your exam readiness.
Exam structure:
| Domain | Weighting | Task Statements |
|---|---|---|
| 1. Fundamentals of AI and ML | 20% |
1.1 Explain basic AI concepts and terminologies. 1.2 Identify practical use cases for AI. 1.3 Describe the ML development lifecycle. |
| 2. Fundamentals of Generative AI | 24% |
2.1 Explain the basic concepts of generative AI. 2.2 Understand the capabilities and limitations of generative AI for solving business problems. 2.3 Describe AWS infrastructure and technologies for building generative AI applications. |
| 3. Applications of Foundation Models | 28% |
3.1 Describe design considerations for applications that use foundation models. 3.2 Choose effective prompt engineering techniques. 3.3 Describe the training and fine-tuning process for foundation models. 3.4 Describe methods to evaluate foundation model performance. |
| 4. Guidelines for Responsible AI | 14% |
4.1 Explain the development of responsible AI systems. 4.2 Recognize the importance of transparent and explainable models. |
| 5. Security, Compliance, and Governance for AI Solutions | 14% |
5.1 Explain methods to secure AI systems. 5.2 Recognize governance and compliance regulations for AI systems. |
Best of luck for your exam! 💪
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