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SAP C_AIG_2412 Exam Syllabus Topics:

TopicDetails
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
  • 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 4
  • 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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q10-Q15):

NEW QUESTION # 10
What advantage can you gain by leveraging different models from multiple providers through the SAP's generative Al hub?

Answer: D

Explanation:
Leveraging different models from multiple providers through SAP's Generative AI Hub offers significant advantages:
1. Access to a Diverse Range of Large Language Models (LLMs):
* Integration with Multiple Providers:SAP's Generative AI Hub provides instant access to a broad spectrum of LLMs from various providers, such as GPT-4 by Azure OpenAI andopen-source models like Falcon-40b.
2. Enhancing Accuracy and Relevance:
* Model Selection Flexibility:By offering a variety of models, developers can select the most suitable one for their specific use cases, thereby enhancing the accuracy and relevance of AI applications that utilize SAP's data assets.
3. Seamless Orchestration and Integration:
* Orchestration Capabilities:The Generative AI Hub enables the orchestration of multiple models, allowing for seamless integration into SAP solutions like SAP S/4HANA and SAP SuccessFactors.


NEW QUESTION # 11
Which of the following executables in generative Al hub works with Anthropic models?

Answer: A


NEW QUESTION # 12
Match the components of a Retrieval Augmented Generation architecture to the diagram.

Answer:

Explanation:

Explanation:
A screenshot of a computer Description automatically generated


NEW QUESTION # 13
Which of the following describes Large Language Models (LLMs)?

Answer: A

Explanation:
Large Language Models (LLMs) are advanced AI systems that leverage deep learning techniques, specifically transformer architectures with self-attention mechanisms, to process and generate human-like text. Option A is incorrect because LLMs do not rely on traditional rule-based systems; they learn patterns from vast datasets. Option C is false as LLMs are designed for text processing, not limited to numerical data. Option D is also inaccurate since LLMs generate responses based on learned patterns, not static templates. Option B is correct, reflecting how LLMs, like those accessible via SAP's Generative AI Hub, use deep learning to understand context, semantics, and generate coherent text for applications such as chatbots, translations, and content creation.


NEW QUESTION # 14
Which of the following capabilities does the generative Al hub provide to developers? Note: There are 2 correct answers to this question.

Answer: B,D

Explanation:
* C. Tools for prompt engineering and experimentation:Generative AI hubs often provide tools and resources to help developers refine their prompts. This is crucial because the quality of the output from a generative AI model heavily depends on how well the prompt is crafted. These tools might include:
* Prompt libraries:Collections of effective prompts for various tasks.
* Prompt testing and analysis:Features to test different prompts and analyze the AI's response.
* Guides and tutorials:Resources to learn about prompt engineering best practices.
* D. Integration of foundation models into applications:Generative AI hubs make it easier for developers to integrate powerful foundation models (large language models like those from Google, OpenAI, etc.) into their own applications. This means developers don't have to build these complex models from scratch. Instead, they can leverage existing models and customize them for their specific needs. This might involve:
* APIs and SDKs:Providing easy-to-use interfaces to access and interact with the foundation models.
* Model customization:Tools to fine-tune existing models on specific datasets or for particular tasks.
* Deployment options:Support for deploying AI models in different environments (cloud, on- premises, etc.).
Why the other options are incorrect:
* A. Proprietary LLMs exclusively:While some generative AI hubs might offer their own proprietary models, they usually provide access to a variety of models, including open-source and those from other providers. This gives developers more flexibility and choice.
* B. Code generation to extend SAP BTP applications:While code generation is a common feature of generative AI, it's not the primary focus of a generative AI hub. The hub's main purpose is to provide access to and facilitate the use of foundation models, not to specifically extend SAP BTP applications.


NEW QUESTION # 15
......

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