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100% Pass SAP - Accurate C-AIG-2412 - SAP Certified Associate - SAP Generative AI Developer Lead2pass

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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 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 2

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 3

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.

Topic 4

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 evaluated.

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q40-Q45):

NEW QUESTION # 40
Where can you configure language models in generative Al hub?

A. The Models tab in Prompt Editor
B. The Orchestration tab in SAP AI Launchpad
C. The Configuration tab of the SAP BTP cockpit
D. The Configuration tab within ML Operations in SAP AI Launchpad

Answer: D

Explanation:
In SAP's Generative AI Hub, configuring language models is a crucial step for integrating AI capabilities into applications.
1. Accessing the Configuration Interface:
* ML Operations Section:Within SAP AI Launchpad, navigate to theML Operationssection to manage machine learning models and operations.
* Configuration Tab:In theConfigurationtab, you can set up and manage various aspects of language models, including selecting model providers, specifying model versions, and configuring deployment settings.
2. Steps to Configure Language Models:
* Model Selection:Choose the desired language model from the available options, such as GPT-4 or other large language models (LLMs) provided through the Generative AI Hub.
* Parameter Configuration:Set parameters like model version, input constraints, and performance settings to tailor the model's behavior to your application's requirements.
* Deployment Setup:Configure deployment details to ensure the model is accessible andintegrated appropriately within your application's infrastructure.

NEW QUESTION # 41
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. Pipeline containers to be used
B. User scripts to manually execute pipeline steps
C. Deployment templates for SAP AI Launchpad
D. Infrastructure resources such as CPUs or GPUs

Answer: A,D

NEW QUESTION # 42
What are some functionalities provided by SAP Al Core? Note: There are 3 correct answers to this question.

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

Answer: A,B,E

NEW QUESTION # 43
Which of the following must you do before connecting to a dataset in order to train a machine learning model in SAP Al Core?
Note: There are 2 correct answers to this question.

A. Grant access rights to the SAP BTP cockpit.
B. Store the dataset in a hyperscaler object store.
C. Store the dataset in the SAP HANA Vector Engine.
D. Provide the storage secret to access the dataset.

Answer: B,D

Explanation:
Before connecting to a dataset for training a machine learning model in SAP AI Core, the following steps are necessary:
* Store the dataset in a hyperscaler object store:Ensure that the dataset is stored in a compatible object storage service provided by a cloud hyperscaler (e.g., AWS S3, Azure Blob Storage) to facilitate seamless access during training.
* Provide the storage secret to access the dataset:Configure the necessary access credentials (storage secrets) within SAP AI Core to securely connect to and retrieve the dataset from the object store.
These steps are essential to establish a secure and efficient connection to the dataset, enabling successful model training within SAP AI Core.

NEW QUESTION # 44
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. Provision SAP AI Core
*Check for foundation model scenario
*Create a configuration
*Create a deployment
D. Run the booster
*Create service keys
*Select the executable ID

Answer: C

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 # 45
......

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