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| Certification Vendor: | Amazon Web Services (AWS) |
|---|---|
| Exam Name: | AWS Certified AI Practitioner |
| Exam Number: | AIF-C01 |
| Related Certifications: | AWS Certified Cloud Practitioner AWS Certified Data Engineer - Associate AWS Certified Machine Learning Engineer - Associate |
| Exam Price: | USD 100 |
| Exam Format: | Multiple choice, Multiple response |
| Available Languages: | English, Simplified Chinese, Korean, Portuguese (Brazil), Japanese |
| Certificate Validity Period: | 3 years |
| Passing Score: | 700 / 1000 |
| Exam Duration: | 90 minutes |
| Real Exam Qty: | 80 |
| Sample Questions: | Amazon AIF-C01 Sample Questions |
| Exam Way: | Online proctored exam (Pearson VUE) or in-person testing center |
| Pre Condition: | None required. Recommended: General IT cloud knowledge and basic understanding of AI/ML concepts. AWS Cloud Practitioner certification is a recommended prerequisite but not mandatory. |
| Official Syllabus URL: | https://aws.amazon.com/certification/certified-ai-practitioner/ |
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NEW QUESTION # 68
A company needs to apply numerical transformations to a set of images to transpose and rotate the images.
Answer: A
Explanation:
The correct answer is B. AWS Lambda can efficiently perform image processing and transformations, such as rotating, resizing, or transposing, in a serverless and event-driven manner. According to AWS documentation, Lambda functions can trigger automatically when new images are uploaded to Amazon S3, perform necessary transformations using libraries like Pillow or OpenCV, and store the processed outputs. This approach minimizes infrastructure management and scales automatically. Deep neural networks (option A) are excessive for simple transformations, while LLMs (option C) and Glue Data Quality (option D) are unrelated-LLMs handle text and Glue is for tabular data validation. Lambda is the AWS-recommended service for lightweight, automated image preprocessing tasks.
Referenced AWS AI/ML Documents and Study Guides:
AWS Lambda Developer Guide - Image Processing Use Cases
AWS ML Specialty Guide - Preprocessing and Automation
NEW QUESTION # 69
An online learning company with large volumes of educational materials wants to use enterprise search.
Which AWS service meets these requirements?
Answer: D
Explanation:
Amazon Kendra is an enterprise search service that uses machine learning to index and search unstructured data such as documents, manuals, and course materials.
Amazon Comprehend performs NLP tasks like sentiment analysis and entity recognition, not enterprise search.
Amazon Textract extracts structured text from scanned docs and PDFs.
Amazon Personalize builds recommendation systems, not search engines.
# Reference:
AWS Documentation - Amazon Kendra
NEW QUESTION # 70
An animation company wants to provide subtitles for its content. Which AWS service meets this requirement?
Answer: C
Explanation:
Amazon Transcribe is the AWS service that converts speech to text, enabling the generation of subtitles (closed captions) for audio and video content automatically.
C is correct:
"Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications." This feature supports creating subtitles and transcripts for media files.
(Reference: Amazon Transcribe Overview, AWS AI Practitioner Official Study Guide) A (Comprehend) is for NLP/text analytics.
B (Polly) is text-to-speech.
D (Translate) translates text, but does not create subtitles from audio/video.
NEW QUESTION # 71
HOTSPOT
Select the correct AI term from the following list for each statement. Each AI term should be selected one time. (Select THREE.)
* AI
* Deep learning
* ML
Answer:
Explanation:
Explanation:
Artificial Intelligence (AI) is the broad field focused on simulating human problem-solving and cognitive abilities, including reasoning, perception, and decision-making.
(Reference: AWS Certified AI Practitioner Official Study Guide)
Machine Learning (ML) is a subset of AI that uses data-driven algorithms to identify patterns and make predictions without explicit programming for each specific task.
(Reference: AWS Machine Learning Overview)
Deep learning is a subset of ML that uses neural networks with many layers (deep neural networks) to process complex data and extract high-level features.
(Reference: AWS Deep Learning on AWS)
NEW QUESTION # 72
A company wants to use a pre-trained generative AI model to generate content for its marketing campaigns. The company needs to ensure that the generated content aligns with the company's brand voice and messaging requirements.
Which solution meets these requirements?
Answer: C
Explanation:
Creating effective prompts is the best solution to ensure that the content generated by a pre-trained generative AI model aligns with the company's brand voice and messaging requirements.
Effective Prompt Engineering:
Involves crafting prompts that clearly outline the desired tone, style, and content guidelines for the model.
By providing explicit instructions in the prompts, the company can guide the AI to generate content that matches the brand's voice and messaging.
Why Option C is Correct:
Guides Model Output: Ensures the generated content adheres to specific brand guidelines by shaping the model's response through the prompt.
Flexible and Cost-effective: Does not require retraining or modifying the model, which is more resource-efficient.
Why Other Options are Incorrect:
A . Optimize the model's architecture and hyperparameters: Improves model performance but does not specifically address alignment with brand voice.
B . Increase model complexity: Adding more layers may not directly help with content alignment.
D . Pre-training a new model: Is a costly and time-consuming process that is unnecessary if the goal is content alignment.
NEW QUESTION # 73
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