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SAP C_AIG_2412 Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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.

Topic 3

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 4

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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q56-Q61):

NEW QUESTION # 56
How does SAP ensure the enterprise-readiness of its Al solutions?

A. By implementing rigorous product standards for Al capabilities
B. By using generic Al models without business context complying with Al ethics standards
C. By ensuring that Al models make bias-free decisions without human input

Answer: A

Explanation:
SAP ensures the enterprise-readiness of its AI solutions through the implementation of rigorous product standards:
1. Rigorous Product Standards for AI Capabilities:
* Development Guidelines:SAP adheres to strict guidelines during the development of AI systems, ensuring they meet high standards of quality, security, and performance.
* Ethical Framework:SAP's AI Ethics Policy governs the development, deployment, use, and sale of AI systems, defining clear ethical rules aligned with global standards.
* Compliance and Governance:SAP has established governance bodies and processes to oversee AI ethics, ensuring that AI solutions are developed and deployed responsibly.

NEW QUESTION # 57
Which of the following steps is NOT a requirement to use the Orchestration service?

A. Modify the underlying Al models
B. Get an auth token for orchestration
C. Create a deployment for orchestration
D. Create an instance of an Al model

Answer: A

Explanation:
To utilize the Orchestration service in SAP's Generative AI Hub, several steps are required; however, modifying the underlying AI models is not among them:
1. Required Steps:
* Get an Auth Token for Orchestration:Obtain authentication credentials to access the orchestration service.
* Create an Instance of an AI Model:Set up an instance of the desired AI model to be used within the orchestration pipeline.
* Create a Deployment for Orchestration:Deploy the configured AI model instance to the orchestration service, enabling it for processing requests.
2. Not Required:
* Modify the Underlying AI Models:The orchestration service allows users to utilize pre-existing AI models without the need to alter their foundational architecture or training.

NEW QUESTION # 58
Which of the following steps must be performed to deploy LLMs in the generative Al hub?

A. Provision SAP AI
* Core Create a configuration
* Run the booster
B. Check for foundation model scenario
* Create a deployment
* Configuring entitlements
C. Run the booster
* Create service keys
* Select the executable ID
D. Provision SAP AI Core
* Check for foundation model scenario
* Create a configuration
* Create a deployment

Answer: D

NEW QUESTION # 59
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
*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
B. 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.
C. 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

Answer: C

Explanation:
SAP recommends the following sequence of steps to effectively solve a business problem using the Generative AI Hub:
1. Create a Basic Prompt in SAP AI Launchpad:
* Initiation:Begin by formulating a simple prompt within SAP AI Launchpad to address the business problem. This serves as the foundation for subsequent refinements.
2. Enhance the Prompts:
* Refinement:Iteratively improve the initial prompt to better capture the nuances of the business problem, ensuring clarity and relevance.
3. Create a Baseline Evaluation Method for the Simple Prompt:
* Establish Metrics:Develop an evaluation framework to assess the performance of the prompt, setting a baseline for comparison as enhancements are made.
4. Evaluate Various Models for the Problem Using generative-ai-hub-sdk:
* Model Assessment:Utilize the generative-ai-hub-sdk to test different large language models (LLMs) against the refined prompt, identifying the model that delivers optimal results.
5. Scale the Solution Using generative-ai-hub-sdk:
* Deployment:Once the optimal model and prompt are determined, employ the generative-ai-hub-sdk to scale the solution, integrating it into the business workflow for widespread application.
Conclusion:
Following this structured approach ensures a methodical development and deployment of AI-driven solutions, enhancing their effectiveness in addressing specific business challenges.

NEW QUESTION # 60
What are some use cases for fine-tuning of a model? Note: There are 2 correct answers to this question.

A. To quickly create iterations on a new use case
B. To sanitize model outputs
C. To customize outputs for specific types of inputs
D. To introduce new knowledge to a model in a resource-efficient way

Answer: C,D

NEW QUESTION # 61
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