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Amazon AIF-C01 Exam Syllabus Topics:

Topic
Details

Topic 1

Guidelines for Responsible AI: This domain highlights the ethical considerations and best practices for deploying AI solutions responsibly, including ensuring fairness and transparency. It is aimed at AI practitioners, including data scientists and compliance officers, who are involved in the development and deployment of AI systems and need to adhere to ethical standards.

Topic 2

Security, Compliance, and Governance for AI Solutions: This domain covers the security measures, compliance requirements, and governance practices essential for managing AI solutions. It targets security professionals, compliance officers, and IT managers responsible for safeguarding AI systems, ensuring regulatory compliance, and implementing effective governance frameworks.

Topic 3

Applications of Foundation Models: This domain examines how foundation models, like large language models, are used in practical applications. It is designed for those who need to understand the real-world implementation of these models, including solution architects and data engineers who work with AI technologies to solve complex problems.

Topic 4

Fundamentals of AI and ML: This domain covers the fundamental concepts of artificial intelligence (AI) and machine learning (ML), including core algorithms and principles. It is aimed at individuals new to AI and ML, such as entry-level data scientists and IT professionals.

Topic 5

Fundamentals of Generative AI: This domain explores the basics of generative AI, focusing on techniques for creating new content from learned patterns, including text and image generation. It targets professionals interested in understanding generative models, such as developers and researchers in AI.

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Amazon AWS Certified AI Practitioner Sample Questions (Q20-Q25):

NEW QUESTION # 20
A company is building a customer service chatbot. The company wants the chatbot to improve its responses by learning from past interactions and online resources.
Which AI learning strategy provides this self-improvement capability?

A. Supervised learning with a manually curated dataset of good responses and bad responses
B. Supervised learning with a continuously updated FAQ database
C. Reinforcement learning with rewards for positive customer feedback
D. Unsupervised learning to find clusters of similar customer inquiries

Answer: C

NEW QUESTION # 21
A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level.
Which solution will meet these requirements?

A. Increase the epochs.
B. Decrease the batch size.
C. Increase the temperature parameter.
D. Decrease the epochs.

Answer: A

NEW QUESTION # 22
An accounting firm wants to implement a large language model (LLM) to automate document processing.
The firm must proceed responsibly to avoid potential harms.
What should the firm do when developing and deploying the LLM? (Select TWO.)

A. Apply prompt engineering techniques.
B. Modify the training data to mitigate bias.
C. Avoid overfitting on the training data.
D. Include fairness metrics for model evaluation.
E. Adjust the temperature parameter of the model.

Answer: B,D

Explanation:
To implement a large language model (LLM) responsibly, the firm should focus on fairness and mitigating bias, which are critical for ethical AI deployment.
* A. Include Fairness Metrics for Model Evaluation:
* Fairness metrics help ensure that the model's predictions are unbiased and do not unfairly discriminate against any group.
* These metrics can measure disparities in model outcomes across different demographic groups, ensuring responsible AI practices.
* C. Modify the Training Data to Mitigate Bias:
* Adjusting training data to be more representative and balanced can help reduce bias in the model's predictions.
* Mitigating bias at the data level ensures that the model learns from a diverse and fair dataset, reducing potential harms in deployment.
* Why Other Options are Incorrect:
* B. Adjust the temperature parameter of the model: Controls randomness in outputs but does not directly address fairness or bias.
* D. Avoid overfitting on the training data: Important for model generalization but not directly related to responsible AI practices regarding fairness and bias.
* E. Apply prompt engineering techniques: Useful for improving model outputs but not specifically for mitigating bias or ensuring fairness.

NEW QUESTION # 23
An education provider is building a question and answer application that uses a generative AI model to explain complex concepts. The education provider wants to automatically change the style of the model response depending on who is asking the question. The education provider will give the model the age range of the user who has asked the question.
Which solution meets these requirements with the LEAST implementation effort?

A. Add a role description to the prompt context that instructs the model of the age range that the response should target.
B. Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user.
C. Summarize the response text depending on the age of the user so that younger users receive shorter responses.
D. Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support.

Answer: A

Explanation:
Adding a role description to the prompt context is a straightforward way to instruct the generative AI model to adjust its response style based on the user's age range. This method requires minimal implementation effort as it does not involve additional training or complex logic.
* Option B (Correct): "Add a role description to the prompt context that instructs the model of the age range that the response should target": This is the correct answer because it involves the least implementation effort while effectively guiding the model to tailor responses according to the age range.
* Option A: "Fine-tune the model by using additional training data" is incorrect because it requires significant effort in gathering data and retraining the model.
* Option C: "Use chain-of-thought reasoning" is incorrect as it involves complex reasoning that may not directly address the need to adjust response style based on age.
* Option D: "Summarize the response text depending on the age of the user" is incorrect because it involves additional processing steps after generating the initial response, increasing complexity.
AWS AI Practitioner References:
* Prompt Engineering Techniques on AWS: AWS recommends using prompt context effectively to guide generative models in providing tailored responses based on specific user attributes.

NEW QUESTION # 24
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?

A. Create a recommendation engine.
B. Develop a multi-language translation system.
C. Build an automatic named entity recognition system.
D. Develop a summarization chatbot.

Answer: D

Explanation:
A summarization chatbot is ideal for extracting key points from legal documents. Large language models (LLMs) can be used to summarize complex texts, such as legal documents, making them more accessible and understandable.
* Option C (Correct): "Develop a summarization chatbot": This is the correct answer because a summarization chatbot uses LLMs to condense and extract key information from text, which is precisely the requirement for reading and summarizing legal documents.
* Option A: "Build an automatic named entity recognition system" is incorrect because it focuses on identifying specific entities, not summarizing documents.
* Option B: "Create a recommendation engine" is incorrect as it is used to suggest products or content, not summarize text.
* Option D: "Develop a multi-language translation system" is incorrect because translation is unrelated to summarizing text.
AWS AI Practitioner References:
* Using LLMs for Text Summarization on AWS: AWS supports developing summarization tools using its AI services, including Amazon Bedrock.

NEW QUESTION # 25
......

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