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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 evolution of large language models, distinguishing them from traditional IT operations analytics. It also explores the current stages of AIOps systems and their implications for organizations. A key skill assessed is understanding the foundational concepts behind LLMs and their applications in various contexts.

Topic 2

SAP AI Core: This section of the exam measures the skills of SAP developers and covers the core components of SAP's AI framework. It emphasizes how these components integrate with existing systems to enhance functionality and performance. Leveraging SAP AI Core to develop intelligent applications that meet business needs is a critical skill that needs to be evaluated.

Topic 3

SAP's Generative AI Hub: This section of the exam measures the skills of technology strategists and covers the functionalities provided by SAP's Generative AI Hub. It emphasizes how organizations can use generative AI to create new content and automate complex tasks. A vital skill evaluated is applying generative AI techniques to enhance business processes and customer experiences.

Topic 4

SAP Business AI: This section of the exam measures the skills of business analysts and covers the features and capabilities of SAP Business AI. It includes exploring how AI can automate processes, provide real-time insights, and enhance decision-making across various business functions.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q11-Q16):

NEW QUESTION # 11
What must be defined in an executable to train a machine learning model using SAP AI Core? Note: There are 2 correct answers to this question.

A. User scripts to manually execute pipeline steps
B. Infrastructure resources such as CPUs or GPUs
C. Pipeline containers to be used
D. Deployment templates for SAP AI Launchpad

Answer: B,C

Explanation:
When training a machine learning model using SAP AI Core, defining an executable requires specifying certain key components to ensure the training process is efficient and effective.
1. Pipeline Containers to Be Used:
* Definition:Pipeline containers encapsulate the environments and dependencies necessary for each step of the machine learning workflow, including data preprocessing, model training, and evaluation.
* Specification in Executable:Within the executable, it's essential to define which pipeline containers will be utilized to ensure that each stage of the training process has the appropriate tools and libraries.

NEW QUESTION # 12
Which statement best describes the Chain-of-Thought (COT) prompting technique?

A. Linking multiple Al models in sequence, where each model's output becomes the input for the next model in the chain.
B. Concatenating multiple related prompts to form a chain, guiding the model through sequential reasoning steps.
C. Writing a series of connected prompts creating a chain of related information.
D. Connecting related concepts by having the LLM generate chains of ideas.

Answer: B

NEW QUESTION # 13
What contract type does SAP offer for Al ecosystem partner solutions?

A. Annual subscription-only contracts
B. Pay-as-you-go for each partner service
C. Bring Your Own License (BYOL) for embedded partner solutions
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 # 14
What are some functionalities provided by SAP Al Core?
Note: There are 3 correct answers to this question.

A. Management of SAP S/4HANA cloud infrastructure
B. Integration of Al services with business applications using a standardized API
C. Monitoring and retraining models in SAP Al Core
D. Orchestration of Al workflows such as model training and inference
E. Continuous delivery and tenant isolation for scalability

Answer: B,D,E

NEW QUESTION # 15
Which of the following steps must be performed to deploy LLMs in the generative Al hub?

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

Answer: A

Explanation:
Deploying Large Language Models (LLMs) in SAP's Generative AI Hub involves a structured process:
1. Provision SAP AI Core:
* Setup:Ensure that SAP AI Core is provisioned in your SAP Business Technology Platform (BTP) account to manage AI workloads.
2. Check for Foundation Model Scenario:
* Validation:Verify the availability of the foundation model scenario within SAP AI Core to confirm that the necessary resources and configurations are in place for deploying LLMs.
3. Create a Configuration:
* Configuration Setup:Define the parameters and settings required for the LLM deployment, including model specifications and resource allocations.
4. Create a Deployment:
* Deployment Execution:Initiate the deployment process within SAP AI Core, making the LLM available for integration and use within your applications.

NEW QUESTION # 16
......

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