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C-AIG-2412 Latest Braindumps Files & Hot C-AIG-2412 Spot Questions

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SAP C-AIG-2412 Exam Syllabus Topics:

Topic
Details

Topic 1

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 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

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 4

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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q54-Q59):

NEW QUESTION # 54
Which of the following are features of the SAP AI Foundation? Note: There are 2 correct answers to this question.

A. Al runtimes and lifecycle management
B. Open source Al model repository
C. Joule integration in SAP SuccessFactors
D. Ready-to-use Al services

Answer: A,D

Explanation:
SAP AI Foundation is an all-in-one AI toolkit that provides developers with the necessary tools to build AI- powered extensions and applications on SAP Business Technology Platform (SAP BTP).
1. Ready-to-Use AI Services:
* Pre-Built AI Capabilities:AI Foundation offers a suite of ready-to-use AI services, enabling developers to integrate AI functionalities into their applications without the need to build models from scratch. These services include capabilities such as document information extraction, translation, and personalized recommendations.
2. AI Runtimes and Lifecycle Management:
* Comprehensive AI Management:AI Foundation provides tools for managing AI runtimes and the entire AI lifecycle, including model deployment, monitoring, and maintenance. This ensures that AI models operate efficiently and remain up-to-date, facilitating seamless integration into business processes.
3. Integration with SAP BTP:
* Unified Platform:By integrating with SAP BTP, AI Foundation allows for the development of AI solutions that are grounded in business data and context, ensuring relevance and reliability in AI-driven applications.

NEW QUESTION # 55
What does SAP recommend you do before you start training a machine learning model in SAP AI Core?
Note: There are 3 correct answers to this question.

A. Perform manual data integration with SAP HANA.
B. Configure the training pipeline using templates.
C. Configure the model deployment in SAP Al Launchpad.
D. Define the required infrastructure resources for training.
E. Register the input dataset in SAP AI Core.

Answer: B,D,E

Explanation:
Before initiating the training of a machine learning model in SAP AI Core, SAP recommends the following steps:
* Configure the training pipeline using templates:Utilize predefined templates to set up the training pipeline, ensuring consistency and efficiency in the training process.
* Define the required infrastructure resources for training:Specify the computational resources, such as CPUs or GPUs, necessary for the training job to ensure optimal performance.
* Register the input dataset in SAP AI Core:Ensure that the dataset intended for training is properly registered within SAP AI Core, facilitating seamless access during the training process.
These preparatory steps are crucial for the successful training of machine learning models within the SAP AI Core environment.

NEW QUESTION # 56
You want to download a json output for a prompt and the response.
Which of the following interfaces can you use in SAP's generative Al hub in SAP AI Launchpad?

A. Chat
B. Administration
C. Prompt Editor
D. Prompt management

Answer: D

NEW QUESTION # 57
You want to download a json output for a prompt and the response.
Which of the following interfaces can you use in SAP's generative Al hub in SAP AI Launchpad?

A. Chat
B. Administration
C. Prompt Editor
D. Prompt management

Answer: D

Explanation:
* Prompt managementis the section within SAP's generative AI hub (accessed via the SAP AI Launchpad) where you work with prompts, including:
* Creating and saving prompts:You can write and store your prompts for later use.
* Viewing prompt history:You can see a record of your past prompts and the AI's responses.
* Exporting prompts and responses:This is where you'd find the option to download your prompt and its corresponding response in JSON format.
Why the other options are incorrect:
* A. Chat:The chat interface is where you have interactive conversations with the generative AI. While you can see your conversation history there, you wouldn't typically find options to download it in JSON format.
* C. Administration:The administration section focuses on managing settings and configurations for the AI hub, not on individual prompts and responses.
* D. Prompt Editor:While a prompt editor might be used to create and refine prompts, it wouldn't necessarily be the place to manage or download them.

NEW QUESTION # 58
What is the primary function of the embedding model in a RAG system?

A. To evaluate the faithfulness and relevance of generated answers
B. To store vector representations of documents and search for relevant passages
C. To encode queries and documents into vector representations for comparison
D. To generate responses based on retrieved documents and user queries

Answer: C

NEW QUESTION # 59
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