AIF-C01 Practice Exam: AWS Certified AI Practitioner
AWS's AI entry cert. Bedrock, SageMaker, LLMs, responsible AI — everything Amazon thinks you should know about AI, tested the AWS way: vaguely.
Practice here, pass there.
What you'll be tested on
- AI & ML Fundamentals
- Generative AI Fundamentals
- Foundation Model Applications
- Responsible AI
- Security & Governance
Sample AIF-C01 questions
A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts. An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders. What should the AI practitioner include in the report to meet the transparency and explainability requirements?
- Code for model training
- Partial dependence plots (PDPs)
- Sample data for training
- Model convergence tables
Show answer
B — Partial dependence plots (PDPs)Partial Dependence Plots (PDPs) are a powerful tool for understanding and explaining how the features in a machine learning model impact predictions. They are often used to meet transparency and explainability requirements for stakeholders. Let's go over why this is the correct choice, along with why the other options are less suitable: Partial Dependence Plots (PDPs) Purpose: PDPs show the relationship between a feature (or multiple features) and the model's predicted output, which helps to explain the effect of each feature on the model’s predictions. Explainability: By visualizing how each feature influences the prediction, stakeholders can better understand how the model works and why it makes certain predictions. This level of interpretability is essential for gaining trust from non-technical stakeholders. Transparency: PDPs improve transparency by providing an intuitive way to analyze and present the effects of individual features.
A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents. Which solution meets these requirements?
- Build an automatic named entity recognition system.
- Create a recommendation engine.
- Develop a summarization chatbot.
- Develop a multi-language translation system.
Show answer
C — Develop a summarization chatbot.A summarization chatbot can effectively read legal documents and generate concise versions that highlight key points. This directly addresses the requirement of extracting essential information, unlike the other options, which focus on different tasks.
A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output. Which ML algorithm meets these requirements?
- Decision trees
- Linear regression
- Logistic regression
- Neural networks
Show answer
A — Decision treesDecision trees provide clear transparency into how the model makes decisions, allowing easy documentation of how the inner mechanism influences the output. The other options do not offer this level of interpretability.
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FAQ
How many practice questions are in this AIF-C01 bank?
452 questions covering the current AIF-C01 AWS Certified AI Practitioner syllabus, every one with the correct answer and an explanation.How long is the real AIF-C01 exam?
The official AIF-C01 exam gives you 90 minutes. Our timed exam mode uses the same limit so the pace feels familiar.What does AIF-C01 access cost?
Plans start at $3.99 for 3 months. One payment, no subscription — and far cheaper than retaking the real exam.