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AIF-C01 Zertifizierung - AIF-C01 Examengine

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Amazon AIF-C01 Prüfungsplan:

Thema
Einzelheiten

Thema 1

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.

Thema 2

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.

Thema 3

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.

Thema 4

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.

Thema 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.

>> AIF-C01 Zertifizierung <<

AIF-C01 Examengine & AIF-C01 Prüfungsübungen

Es gibt ein Sprichwort, das Spiel beendet, wenn Sie es aufgeben. Die Prüfung ist ähnlich wie das Spiel. Viele geben die Amazon AIF-C01 Zertifizierungsprüfungen auf, wenn sie nicht genug Zeit haben. Aber Sie können AIF-C01 Prüfung mit guter Note bestehen, wenn Sie die richtige exam Fragen benutzen trotz kurzer Zeit. Glauben Sie nicht? Dann müssen sie die AIF-C01 Prüfungsunterlagen von ITZert probieren.

Amazon AWS Certified AI Practitioner AIF-C01 Prüfungsfragen mit Lösungen (Q10-Q15):

10. Frage
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?

A. Partial dependence plots (PDPs)
B. Model convergence tables
C. Sample data for training
D. Code for model training

Antwort: A

11. Frage
Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?

A. Measure the model's accuracy against a predefined benchmark dataset.
B. Calculate the total cost of resources used by the model.
C. Count the number of layers in the neural network.
D. Assess the color accuracy of images processed by the model.

Antwort: A

Begründung:
Measuring the model's accuracy against a predefined benchmark dataset is the correct strategy to evaluate the accuracy of a foundation model (FM) used in image classification tasks.
* Model Accuracy Evaluation:
* In image classification, the accuracy of a model is typically evaluated by comparing the predicted labels with the true labels in a benchmark dataset that is representative of the real-world data the model will encounter.
* This approach provides a quantifiable measure of how well the model performs on known data and is a standard practice in machine learning.
* Why Option B is Correct:
* Benchmarking Accuracy: Using a predefined dataset allows for consistent and reliable evaluation of model performance.
* Standard Practice: It is a widely accepted method for assessing the effectiveness of image classification models.
* Why Other Options are Incorrect:
* A. Total cost of resources: Does not measure model accuracy but rather the cost of operation.
* C. Number of layers in the neural network: Does not directly correlate with the accuracy or performance of the model.
* D. Color accuracy of images processed by the model: Is unrelated to the model's classification accuracy.

12. Frage
A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.
Which type of model meets this requirement?

A. BERT-based models
B. Clustering models
C. Prescriptive ML models
D. Topic modeling

Antwort: A

13. Frage
A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix.
Which solution scope gives the company the MOST ownership of security responsibilities?

A. Building an application by using an existing third-party generative AI foundation model (FM).
B. Using a third-party enterprise application that has embedded generative AI features.
C. Building and training a generative AI model from scratch by using specific data that a customer owns.
D. Refining an existing third-party generative AI foundation model (FM) by fine-tuning the model by using data specific to the business.

Antwort: C

Begründung:
Building and training a generative AI model from scratch provides the company with the most ownership and control over security responsibilities. In this scenario, the company is responsible for all aspects of the security of the data, the model, and the infrastructure.
* Option D (Correct): "Building and training a generative AI model from scratch by using specific data that a customer owns": This is the correct answer because it involves complete ownership of the model, data, and infrastructure, giving the company the highest level of responsibility for security.
* Option A: "Using a third-party enterprise application that has embedded generative AI features" is incorrect as the company has minimal control over the security of the AI features embedded within a third-party application.
* Option B: "Building an application using an existing third-party generative AI foundation model (FM)" is incorrect because security responsibilities are shared with the third-party model provider.
* Option C: "Refining an existing third-party generative AI FM by fine-tuning the model with business- specific data" is incorrect as the foundation model and part of the security responsibilities are still managed by the third party.
AWS AI Practitioner References:
* Generative AI Security Scoping Matrix on AWS: AWS provides a security responsibility matrix that outlines varying levels of control and responsibility depending on the approach to developing and using AI models.

14. Frage
A company wants to develop an educational game where users answer questions such as the following: "A jar contains six red, four green, and three yellow marbles. What is the probability of choosing a green marble from the jar?" Which solution meets these requirements with the LEAST operational overhead?

A. Use reinforcement learning to train a model to return the probability.
B. Use supervised learning to create a regression model that will predict probability.
C. Use code that will calculate probability by using simple rules and computations.
D. Use unsupervised learning to create a model that will estimate probability density.

Antwort: C

15. Frage
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