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SAP C-AIG-2412 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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.

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q17-Q22):

NEW QUESTION # 17
What contract type does SAP offer for Al ecosystem partner solutions?

A. Bring Your Own License (BYOL) for embedded partner solutions
B. Pay-as-you-go for each partner service
C. Annual subscription-only contracts
D. All-in-one contracts, with services that are contracted through SAP

Answer: D

Explanation:
SAP collaborates with a wide ecosystem of partners, including leading general-purpose AI vendors, to provide tailored solutions to its customers. Through the SAP Store, customers have access to numerous partner applications and a variety of tools, allowing them to choose solutions that best fit their requirements.
Contractual Approach:
* All-in-One Contracts:SAP offers all-in-one contracts for AI ecosystem partner solutions, where services are white-labeled and contracted directly through SAP. This approach simplifies the procurement process for customers, as they engage with SAP as the single point of contact for both SAP and partner services.
* Exclusion of Bring Your Own License (BYOL) Model:SAP does not adopt a "bring your own license" model for these embedded partner solutions. Instead, all services are integrated and provided under unified contracts managed by SAP.
Benefits of This Contractual Model:
* Simplified Procurement:Customers benefit from a streamlined purchasing process, dealing with a single contract and point of contact for multiple services.
* Integrated Solutions:The all-in-one contract ensures that partner solutions are seamlessly integrated with SAP's offerings, providing a cohesive experience.
* Assured Compliance and Support:By contracting through SAP, customers can be confident in the compliance, security, and support standards upheld across all services.

NEW QUESTION # 18
What is a part of LLM context optimization?

A. Enhancing the computational speed of the model
B. Providing the model with domain-specific knowledge needed to solve a problem
C. Reducing the model's size to improve efficiency
D. Adjusting the model's output format and style

Answer: B

Explanation:
LLM context optimization involves tailoring a Large Language Model's (LLM) input context to enhance its performance on specific tasks, particularly by incorporating domain-specific knowledge.
1. Understanding LLM Context Optimization:
* Definition:Context optimization refers to the process of adjusting the input provided to an LLM to ensure it includes relevant information, thereby enabling the model to generate more accurate and contextually appropriate outputs.
* Domain-Specific Knowledge Integration:By embedding domain-specific information into the model's context, the LLM can better understand and address specialized queries, leading to improved problem- solving capabilities.
2. Importance of Domain-Specific Knowledge:
* Enhanced Relevance:Providing domain-specific context ensures that the model'sresponses are pertinent to the particular field or subject matter, increasing the utility of the generated content.
* Improved Accuracy:With access to specialized knowledge, the LLLM is less likely to produce generic or incorrect answers, thereby enhancing the overall quality of its outputs.
3. Methods of Context Optimization:
* Prompt Engineering:Crafting prompts that include necessary domain-specific information to guide the model towards generating desired responses.
* Retrieval-Augmented Generation (RAG):Incorporating external data sources into the model's context to provide up-to-date and relevant information pertinent to the domain.

NEW QUESTION # 19
What are some components of the training pipeline in SAP AI Core?
Note: There are 2 correct answers to this question.

A. Input datasets stored in a hyperscaler object store
B. Automated deployment to Kubernetes clusters
C. Executables that define the training process
D. The SAP HANA database for model storage

Answer: A,C

NEW QUESTION # 20
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 # 21
Which of the following is a benefit of using Retrieval Augmented Generation?

A. It allows LLMs to access and utilize information beyond their initial training data.
B. It reduces the computational resources required for language modeling.
C. It eliminates the need for fine-tuning LLMs for specific tasks.
D. It enables LLMs to learn new languages without additional training.

Answer: A

NEW QUESTION # 22
......

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New C-AIG-2412 Exam Vce - C-AIG-2412 New Dumps Free

SAP Certified Associate - SAP Generative AI Developer Study Training Dumps Grasp the Core Knowledge of C-AIG-2412 Exam - TrainingDump

SAP C-AIG-2412 Exam Syllabus Topics:

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q17-Q22):

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