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Amazon AI1-C01 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamentals of Generative AI | 24% | - Generative AI Capabilities
|
| Guidelines for Responsible AI | 14% | - Ethical AI Development
|
| Applications of Foundation Models | 28% | - Building AI Solutions
|
| Security, Compliance, and Governance for AI Solutions | 14% | - AI Security
|
| Fundamentals of AI and ML | 20% | - AI and ML Concepts
|
Amazon AWS Certified AI Practitioner Sample Questions:
1. A company is building a solution to generate images for protective eyewear. The solution must have high accuracy and must minimize the risk of incorrect annotations.
Which solution will meet these requirements?
A) Human-in-the-loop validation by using Amazon SageMaker Ground Truth Plus
B) Data augmentation by using an Amazon Bedrock knowledge base
C) Image recognition by using Amazon Rekognition
D) Data summarization by using Amazon QuickSight
2. A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data.
Which strategy will successfully fine-tune the model?
A) Provide labeled data with the prompt field and the completion field.
B) Train the model on journals and textbooks.
C) Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
D) Purchase Provisioned Throughput for Amazon Bedrock.
3. A company built a deep learning model for object detection and deployed the model to production.
Which AI process occurs when the model analyzes a new image to identify objects?
A) Inference
B) Bias correction
C) Model deployment
D) Training
4. A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.
Which business objective should the company use to evaluate the effect of the LLM chatbot?
A) Website engagement rate
B) Average call duration
C) Corporate social responsibility
D) Regulatory compliance
5. A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals.
Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?
A) Benchmark datasets
B) Content moderation guidelines
C) Moderation logs
D) User-generated content
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: A |






