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C-AIG-2412 Latest Exam Guide & Certification C-AIG-2412 Book Torrent

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C-AIG-2412 Latest Exam Guide & Certification C-AIG-2412 Book Torrent

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SAP C-AIG-2412 Exam Syllabus Topics:
TopicDetails
Topic 1
  • SAP AI Core: This section of the exam measures the skills of AI Developers and covers the fundamental components of SAP AI Core. Candidates are assessed on their ability to work with the core services that allow machine learning models to be deployed and managed within SAP environments. The focus is on understanding how AI Core fits into SAP’s ecosystem and ensures smooth integration with enterprise applications.
Topic 2
  • Advanced AI Techniques with SAP’s Generative AI Hub: This section of the exam measures the skills of Solution Architects and covers advanced techniques available through SAP’s Generative AI Hub. Candidates are assessed on their ability to design, optimize, and scale generative AI solutions that go beyond basic implementations. The focus includes applying sophisticated strategies to integrate advanced models, manage performance, and align AI-driven outcomes with complex enterprise goals.
Topic 3
  • Large Language Models (LLMs): This section of the exam measures the skills of AI Developers and covers the practical use of large language models in SAP environments. Candidates are expected to understand how LLMs can be applied to automate tasks, enhance decision-making, and improve user interaction within SAP systems. The exam evaluates knowledge of handling model selection, fine-tuning, and adapting LLMs to specific business cases.
Topic 4
  • SAP's Generative AI Hub: This section of the exam measures the skills of Solution Architects and covers SAP’s Generative AI Hub, which acts as the central layer for designing and managing generative AI solutions. The exam tests knowledge of building, deploying, and connecting AI models to business scenarios through the Hub. Emphasis is placed on leveraging the Hub to streamline workflows and ensure scalable solutions that align with organizational needs.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q52-Q57):NEW QUESTION # 52
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. Define the LLM
  • B. Create the Orchestration Configuration
  • C. Run the Orchestration Request
  • D. Define the Template and Default Input Values
Answer: A
Explanation:
The provided code snippet defines a Large Language Model (LLM) within the SAP Generative AI Hub SDK's orchestration service:
from gen_ai_hub.orchestration.models.llm import LLM
llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2})
1. Importing the LLM Class:
* Code:from gen_ai_hub.orchestration.models.llm import LLM
* Purpose:Imports the LLM class from the SDK, enabling the creation of an LLM instance.
2. Defining the LLM Instance:
* Code:llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature":
0.2})
* Parameters:
* name:Specifies the model's name, in this case, "gpt-40".
* version:Indicates the model version, set to "latest" to use the most recent version.
* parameters:A dictionary defining model-specific parameters:
* max_tokens:Sets the maximum number of tokens (words or word pieces) the model can generate, here limited to 256 tokens.
* temperature:Controls the randomness of the output; a lower value like 0.2 results in more deterministic responses.
3. Role in Orchestration Pipeline:
* Function:This definition is a crucial step in the orchestration pipeline, specifying which LLM to use and configuring its behavior for subsequent tasks.
Conclusion:
The code snippet defines an LLM named "gpt-40" with specific parameters, preparing it for integration into an AI-driven workflow within SAP's Generative AI Hub.

NEW QUESTION # 53
What are some metrics to evaluate the effectiveness of a Retrieval Augmented Generation system? Note: There are 2 correct answers to this question.
  • A. Carbon footprint
  • B. Relevance
  • C. Speed
  • D. Faithfulness
Answer: B,D

NEW QUESTION # 54
How does the Al API support SAP AI scenarios? Note: There are 2 correct answers to this question.
  • A. By managing Kubernetes clusters automatically
  • B. By integrating Al models into third-party platforms like AWS
  • C. By providing a unified framework for operating Al services
  • D. By integrating Al services into business applications
Answer: C,D
Explanation:
The AI API in SAP plays a crucial role in supporting AI scenarios by facilitating the integration of AI services into business applications and providing a unified framework for operating these services.
1. Integration of AI Services into Business Applications:
* Seamless Integration:The AI API enables developers to incorporate AI functionalities directly into SAP and non-SAP business applications, enhancing their capabilities with intelligent features.
* Use Case Example:Integrating AI models into SAP Build Apps allows for the creation of AI-powered applications that can perform tasks such as data analysis, predictive modeling, and more.
2. Unified Framework for Operating AI Services:
* Standardized Operations:The AI API provides a consistent and standardized framework for managing AI services, ensuring uniformity in deployment, monitoring, and maintenance across different platforms.
* Scalability and Flexibility:This unified approach allows for scalable AI operations, accommodating various AI models and services within a cohesive operational structure.

NEW QUESTION # 55
What is a significant risk associated with using LLMs?
  • A. Potential biases in generated content
  • B. Inability to generate text in multiple languages
  • C. Unlimited processing power usage without cost control
  • D. Complete elimination of human oversight in content creation
Answer: A
Explanation:
A significant risk of using LLMs is the potential for biases in generated content, stemming from biases present in their training data. Option A is incorrect because LLMs do not inherently eliminate human oversight; oversight is often maintained, especially in enterprise settings like SAP's. Option B is false as LLMs can generate text in multiple languages, as seen with models like GPT-4. Option D, while a concern in terms of resource management, is not the most significant risk compared to bias, and cost control can be implemented. Option C is correct because biased outputs can lead to unfair decisions or misinformation, a risk SAP mitigates through its AI Ethics framework, which includes principles like avoiding bias and discrimination, ensuring responsible AI deployment.

NEW QUESTION # 56
Which of the following sequence of steps does SAP recommend you use to solve a business problem using generative Al hub?
  • A. Create a basic prompt in SAP AI Launchpad
    *         Evaluate various models for the problem using generative-ai-hub-sdk
    *         Scale the solution using generative-ai-hub-sdk
    *         Create a baseline evaluation method for the simple prompt
    *         Enhance the prompts.
  • B. Create a basic prompt in SAP AI Launchpad
    *         Enhance the prompts
    *         Create a baseline evaluation method for the simple prompt
    *         Evaluate various models for the problem using generative-ai-hub-sdk
    *         Scale the solution using generative-ai-hub-sdk
  • C. Create a basic prompt in SAP AI Launchpad
    *         Scale the solution using generative-ai-hub-sdk
    *         Create a baseline evaluation method for the simple prompt
    *         Enhance the prompts
    *         Evaluate various models for the problem using generative-ai-hub-sdk
Answer: B

NEW QUESTION # 57
......
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