Easy AIF-C01 practice questions
Direct recall — confirm you know the core facts and definitions. 10 easy questions available — no sign-up, always free.
A software engineering team wants to accelerate development by using a generative-AI assistant that can generate code suggestions, explain existing code, and help identify security issues directly within their IDE. Which AWS service is purpose-built for this use case?
A software engineering team wants an AI assistant that is purpose-built to help developers write, debug, and explain application code directly inside their IDE, with minimal setup and no need to build a custom application. Which AWS generative-AI offering is designed specifically for this purpose?
A startup wants to add generative-AI features to its customer support app by calling multiple third-party foundation models (from providers like Anthropic and Meta) through a single API. The team has no ML infrastructure and wants to avoid managing servers, provisioning GPUs, or hosting the models themselves. Which AWS service best meets these requirements?
A startup wants to build a chatbot, a document summarizer, and a code-completion tool. Their small team has no ML expertise and cannot afford to train models from scratch. During planning, an engineer explains that a single type of model can serve as the starting point for all three applications because it was trained on vast, diverse data and can be adapted to many tasks. Which characteristic best describes this type of model?
A retail company wants to rapidly produce dozens of unique product background images for a seasonal ad campaign. Their small design team cannot manually create this volume in time. Which capability of generative AI foundation models best addresses this need?
A marketing team wants to automatically produce unique first-draft product descriptions and promotional blog posts based on short prompts describing each new product. They want the system to generate original, human-like text rather than sorting existing content into categories. Which type of AI capability is most appropriate for this task?
A logistics company has trained an ML model that classifies package damage from photos. The model is now deployed, and every time a warehouse worker uploads a new photo, the system returns a damage/no-damage prediction within a second. In ML terminology, what is happening when the model generates a prediction for each newly uploaded photo?
A retail analytics team is starting a new project to predict which products will sell out during seasonal promotions. They have identified the business goal and success metrics. Their next step is to gather three years of point-of-sale records, promotion calendars, and inventory logs from different databases, then clean inconsistent formats and handle missing values before any modeling begins. Which phase of the ML development lifecycle does this work primarily represent?
A data analyst wants a foundation model on Amazon Bedrock to classify customer reviews as positive, negative, or neutral. They write a single instruction: 'Classify the sentiment of the following review as positive, negative, or neutral,' followed by the review text — without providing any sample reviews and their labels. Which prompt engineering technique does this describe?
A developer is preparing input text for a large language model on Amazon Bedrock. Before the model can process the sentence 'Generative AI is transforming business,' the text must first be broken down into smaller units that the model can numerically represent and process. What is the term for these smaller units, and what step produces them?