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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	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.
Topic 3	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 4	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.

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q53-Q58):

NEW QUESTION # 53
What are some components of the training pipeline in SAP AI Core? Note: There are 2 correct answers to this question.

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

Answer: B,D

Explanation:
The training pipeline in SAP AI Core comprises several key components that facilitate the development and deployment of machine learning models.
1. Input Datasets Stored in a Hyperscaler Object Store:
* Data Storage:Input datasets are often stored in hyperscaler object stores, which provide scalable and secure storage solutions. These datasets serve as the foundational data for training machine learning models.
* Integration:SAP AI Core integrates with various hyperscaler object stores, allowing seamless access to training data during the model development process.

NEW QUESTION # 54
What are some benefits of the SAP AI Launchpad? Note: There are 2 correct answers to this question.

A. Simplified model retraining and performance improvement.
B. Centralized Al lifecycle management for all Al scenarios.
C. Direct deployment of Al models to SAP HANA.
D. Integration with non-SAP platforms like Azure and AWS.

Answer: A,B

NEW QUESTION # 55
What are some benefits of the SAP AI Launchpad? Note: There are 2 correct answers to this question.

A. Direct deployment of Al models to SAP HAN
B. Simplified model retraining and performance improvement.
C. Centralized Al lifecycle management for all Al scenarios.
D. Integration with non-SAP platforms like Azure and AWS.

Answer: B,C

NEW QUESTION # 56
What are some advantages of using agents in training models? Note: There are 2 correct answers to this question.

A. To guarantee accurate decision making in complex scenarios
B. To eliminate the need for human oversight
C. To improve the quality of results
D. To streamline LLM workflows

Answer: C,D

NEW QUESTION # 57
What are some components of the training pipeline in SAP AI Core?
Note: There are 2 correct answers to this question.

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

Answer: B,D

NEW QUESTION # 58
......

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C_AIG_2412 New Learning Materials - C_AIG_2412 Study Material

C_AIG_2412 Test Preparation: SAP Certified Associate - SAP Generative AI Developer & C_AIG_2412 Exam Lab Questions

SAP C_AIG_2412 Exam Syllabus Topics:

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q53-Q58):

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