C-AIG-2412認証試験の問題集解答を提供しています [2025年10月]
更新されたC-AIG-2412試験練習テスト問題
SAP C-AIG-2412 認定試験の出題範囲：
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質問 # 28
You want to extract useful information from customer emails to augment existing applications in your company.
How can you use generative-ai-hub-sdk in this context?
- A. Generate random email content and send them to customers.
- B. Train custom models based on the mail data.
- C. Generate JSON strings based on extracted information.
- D. Generate a new SAP application based on the mail data.
正解：C
質問 # 29
Where can you configure language models in generative Al hub?
- A. The Orchestration tab in SAP AI Launchpad
- B. The Configuration tab of the SAP BTP cockpit
- C. The Configuration tab within ML Operations in SAP AI Launchpad
- D. The Models tab in Prompt Editor
正解：C
質問 # 30
What contract type does SAP offer for Al ecosystem partner solutions?
- A. Pay-as-you-go for each partner service
- B. Annual subscription-only contracts
- C. All-in-one contracts, with services that are contracted through SAP
- D. Bring Your Own License (BYOL) for embedded partner solutions
正解：A、B、C
質問 # 31
Which of the following is a benefit of using Retrieval Augmented Generation?
- A. It reduces the computational resources required for language modeling.
- B. It enables LLMs to learn new languages without additional training.
- C. It eliminates the need for fine-tuning LLMs for specific tasks.
- D. It allows LLMs to access and utilize information beyond their initial training data.
正解：D
質問 # 32
Which neural network architecture is primarily used by LLMs?
- A. Convolutional Neural Networks (CNNs)
- B. Transformer architecture with self-attention mechanisms
- C. Sequential encoder-decoder architecture
- D. Recurrent neural network architecture
正解：B
質問 # 33
What are some advantages of using agents in training models? Note: There are 2 correct answers to this question.
- A. To improve the quality of results
- B. To streamline LLM workflows
- C. To eliminate the need for human oversight
- D. To guarantee accurate decision making in complex scenarios
正解：A、B
解説：
Incorporating agents into the training and deployment of Large Language Models (LLMs) offers notable advantages:
1. Improving the Quality of Results:
* Specialized Task Handling:Agents can be designed to manage specific tasks or subtasks within a larger process, ensuring that each component is handled with expertise, thereby enhancing the overall quality of the output.
* Error Reduction:By delegating particular functions to specialized agents, the likelihood of errors decreases, leading to more accurate and reliable results.
2. Streamlining LLM Workflows:
* Process Automation:Agents can automate repetitive or time-consuming tasks within the LLM workflow, increasing efficiency and allowing human resources to focus on more complex aspects of model development and deployment.
* Workflow Management:Agents facilitate the coordination of various stages in the LLM pipeline, ensuring seamless transitions between tasks and improving overall workflow efficiency.
3. Enhancing Model Performance:
* Adaptive Learning:Agents can monitor model performance and implement adjustments in real-time, promoting continuous improvement and adaptability to new data or requirements.
* Resource Optimization:By managing specific tasks, agents help in optimizing computational resources, ensuring that the LLM operates efficiently without unnecessary expenditure of processing power.
質問 # 34
What are some benefits of using an SDK for evaluating prompts within the context of generative Al? Note: There are 3 correct answers to this question.
- A. Automating prompt testing across various scenarios
- B. Supporting low code evaluations using graphical user interface
- C. Providing metrics to quantitatively assess response quality
- D. Maintaining data privacy by using data masking techniques
- E. Creating custom evaluators that meet specific business needs
正解：A、C、E
質問 # 35
What advantage can you gain by leveraging different models from multiple providers through the SAP's generative Al hub?
- A. Design new product interfaces for SAP applications
- B. Get more training data for new models
- C. Train new models using SAP and non-SAP data
- D. Enhance the accuracy and relevance of Al applications that use SAP's data assets
正解：D
質問 # 36
What does the Prompt Management feature of the SAP AI launchpad allow users to do?
- A. Interact with models through a conversational interface
- B. Provide personalized user interactions
- C. Create and edit prompts
- D. Access and manage saved prompts and their versions
正解：C、D
解説：
The Prompt Management feature within SAP AI Launchpad's Generative AI Hub offers users comprehensive tools for handling prompts throughout their lifecycle:
1. Create and Edit Prompts:
* Prompt Editor:Users can utilize the Prompt Editor to craft and modify prompts, facilitating effective prompt engineering and experimentation.
2. Access and Manage Saved Prompts and Their Versions:
* Prompt Lifecycle Management:The platform provides capabilities to manage the lifecycle of prompts, including accessing saved prompts, tracking their versions, and organizing them for efficient reuse and iteration.
Conclusion:
SAP AI Launchpad's Prompt Management feature empowers users to create, edit, and manage prompts effectively, supporting robust prompt engineering and lifecycle management within the Generative AI Hub.
質問 # 37
What is one primary benefit of using LLMs in business applications?
- A. They require no maintenance or updates once implemented
- B. They replace the need for human decision-making entirely
- C. They eliminate all data privacy concerns in business operations
- D. They enhance automation and scalability of processes
正解：D
解説：
The primary benefit of using LLMs in business applications is their ability to enhance automation and scalability, making processes more efficient and adaptable to large-scale needs. Option A is incorrect because LLMs augment, rather than fully replace, human decision-making-human oversight remains critical. Option B is false as LLMs do not inherently eliminate privacy concerns; data privacy must still be managed (e.g., through SAP's privacy-preserving techniques like differential privacy). Option C is inaccurate since LLMs require ongoing maintenance, updates, and monitoring to remain effective. Option D is correct because LLMs automate tasks like document processing, content generation, and customer interaction, while their scalability allows businesses to handle increasing data volumes and user demands efficiently, as seen in SAP's integration with tools like Joule and SAP Business AI.
質問 # 38
What are some components of the training pipeline in SAP AI Core? Note: There are 2 correct answers to this question.
- A. The SAP HANA database for model storage
- B. Executables that define the training process
- C. Automated deployment to Kubernetes clusters
- D. Input datasets stored in a hyperscaler object store
正解：B、D
解説：
The training pipeline in SAP AI Core comprises several key components that facilitate the development and deployment of machine learning models.
1. Input Datasets Stored in a Hyperscaler Object Store:
* Data Storage:Input datasets are often stored in hyperscaler object stores, which provide scalable and secure storage solutions. These datasets serve as the foundational data for training machine learning models.
* Integration:SAP AI Core integrates with various hyperscaler object stores, allowing seamless access to training data during the model development process.
質問 # 39
How can Joule improve workforce productivity? Note: There are 2 correct answers to this question.
- A. By resolving hardware malfunctions.
- B. By offering generic task recommendations unrelated to specific roles.
- C. By providing context-based role-specific task assistance.
- D. By maintaining strict adherence to data privacy regulations.
正解：C、D
質問 # 40
What are some benefits of the SAP AI Launchpad? Note: There are 2 correct answers to this question.
- A. Direct deployment of Al models to SAP HAN
- B. Simplified model retraining and performance improvement.
- C. Centralized Al lifecycle management for all Al scenarios.
- D. Integration with non-SAP platforms like Azure and AWS.
正解：B、C
質問 # 41
What can be done once the training of a machine learning model has been completed in SAP AI Core? Note: There are 2 correct answers to this question.
- A. The model can be deployed for inferencing.
- B. The model's accuracy can be optimized directly in SAP HANA.
- C. The model can be registered in the hyperscaler object store.
- D. The model can be deployed in SAP HAN
正解：A、C
質問 # 42
How do resource groups in SAP AI Core improve the management of machine learning workloads? Note: There are 2 correct answers to this question.
- A. They enhance pipeline execution speeds through workload distribution.
- B. They enable simultaneous orchestration of Kubernetes clusters.
- C. They provide isolation for datasets and Al artifacts.
- D. They ensure workload separation for different tenants or departments.
正解：C、D
質問 # 43
What is the goal of prompt engineering?
- A. To develop new neural network architectures for Al models
- B. To craft inputs that guide Al systems in generating desired outputs
- C. To optimize hardware performance for Al computations
- D. To replace human decision-making with automated processes
正解：B
解説：
Prompt engineering involves designing and refining inputs, known as prompts, to effectively guide AI systems, particularly Large Language Models (LLMs), in producing desired outputs.
1. Understanding Prompt Engineering:
* Definition:Prompt engineering is the process of creating and optimizing prompts to elicit specific responses from AI models. It serves as a crucial interface between human intentions and machine- generated content.
* Purpose:The primary goal is to communicate the task requirements clearly to the AI model, ensuring that the generated output aligns with user expectations.
2. Importance in AI Systems:
* Guiding AI Behavior:Well-crafted prompts can direct AI models to perform a wide range of tasks, from answering questions to generating creative content, by setting the context and specifying the desired format of the output.
* Enhancing Output Quality:Effective prompt engineering can improve the relevance, coherence, and accuracy of AI-generated responses, making AI systems more useful and reliable in practical applications.
3. Application in SAP's Generative AI Hub:
* Prompt Management:SAP's Generative AI Hub provides tools for prompt management, allowing developers to create, edit, and manage prompts to interact with various AI models efficiently.
* Exploration and Development:The hub offers features like prompt editors and AI playgrounds, enabling users to experiment with different prompts and models to achieve optimal results for their specific use cases.
質問 # 44
What are the benefits of SAP's generative Al hub?
Note: There are 2 correct answers to this question.
- A. Build custom Al solutions and extend SAP applications
- B. Accelerate Al development with flexible access to a broad range of models
- C. Provide libraries for no-code development
- D. Send your data to various LLM providers for training feedback
正解：A、B
質問 # 45
Which of the following techniques uses a prompt to generate or complete subsequent prompts (streamlining the prompt development process), and to effectively guide Al model responses?
- A. Meta prompting
- B. One-shot prompting
- C. Few-shot prompting
- D. Chain-of-thought prompting
正解：A
解説：
Meta prompting is a technique in prompt engineering where a prompt is designed to generate or refine subsequent prompts.
1. Definition and Purpose:
* Streamlining Prompt Development:Meta prompting automates the creation of effective prompts by utilizing AI to generate or enhance them, thereby streamlining the prompt development process.
* Guiding AI Model Responses:By generating refined prompts, meta prompting effectively guides AI models to produce more accurate and contextually relevant responses.
2. Application in SAP's Generative AI Hub:
* Prompt Engineering Tools:SAP's Generative AI Hub provides tools that support advanced prompt engineering techniques, including meta prompting, to enhance AI model interactions.
質問 # 46
What is the goal of prompt engineering?
- A. To develop new neural network architectures for Al models
- B. To craft inputs that guide Al systems in generating desired outputs
- C. To optimize hardware performance for Al computations
- D. To replace human decision-making with automated processes
正解：B
質問 # 47
Which of the following are grounding principles included in SAP's AI Ethics framework? Note: There are 3 correct answers to this question.
- A. Store all user data for legal proceedings
- B. Human agency and oversight
- C. Avoid bias and discrimination
- D. Maximize business profits
- E. Transparency and explainability
正解：B、C、E
解説：
SAP's AI Ethics framework is built upon several grounding principles to ensure responsible AI development and deployment:
1. Transparency and Explainability:
* Definition:Ensuring that AI systems are understandable and their decision-making processes can be clearly explained to stakeholders.
* Implementation:SAP commits to making AI systems transparent, providing clearinformation about how decisions are made to build trust and facilitate accountability.
2. Human Agency and Oversight:
* Definition:Maintaining human control over AI systems, ensuring that humans can intervene or oversee AI operations as necessary.
* Implementation:SAP emphasizes the importance of human oversight in AI applications, ensuring that AI augments human decision-making rather than replacing it.
3. Avoid Bias and Discrimination:
* Definition:Preventing AI systems from perpetuating or amplifying biases, ensuring fair and equitable treatment for all users.
* Implementation:SAP strives to develop AI systems that are free from bias, implementing measures to detect and mitigate discriminatory outcomes.
質問 # 48
Which of the following steps is NOT a requirement to use the Orchestration service?
- A. Create a deployment for orchestration
- B. Get an auth token for orchestration
- C. Create an instance of an Al model
- D. Modify the underlying Al models
正解：D
質問 # 49
You want to use the orchestration service through SAP's generative-Al-hub-sdk.
What does the following code do?
from gen_ai_hub.orchestration.models.11m import LLM
11m =
LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2})
- A. Create the Orchestration Configuration
- B. Run the Orchestration Request
- C. Define the Template and Default Input Values
- D. Define the LLM
正解：D
質問 # 50
What capabilities does the Exploration and Development feature of the generative Al hub provide? Note:
There are 2 correct answers to this question.
- A. Al playground and chat
- B. Automatic model selection
- C. Develop and debug ABAP code
- D. Prompt editor and management
正解：A、D
解説：
The Exploration and Development feature of SAP's Generative AI Hub provides several capabilities to facilitate AI solution development:
1. AI Playground and Chat:
* Interactive Environment:The AI playground offers an interactive space for developers to experiment with various AI models, test prompts, and observe outputs in real-time.
* Conversational Interface:The chat functionality enables users to engage in dialogue with AI models, refining prompts and understanding model behavior through iterative interactions.
2. Prompt Editor and Management:
* Prompt Creation:The prompt editor allows developers to craft and modify prompts tailored to specific business needs, enhancing the precision of AI responses.
* Prompt Organization:Prompt management tools facilitate the organization, versioning, and storage of prompts, ensuring efficient retrieval and reuse in various projects.
質問 # 51
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検証済みのC-AIG-2412問題集と解答を使って100%一発合格保証で更新された問題集：https://drive.google.com/open?id=1DEBoqEVgaQxHDKL5qsAblhVVPNpUcbTf
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