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SAP C_AIG_2412 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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'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 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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q18-Q23):

NEW QUESTION # 18
How do resource groups in SAP AI Core improve the management of machine learning workloads? Note:
There are 2 correct answers to this question.

A. They ensure workload separation for different tenants or departments.
B. They enable simultaneous orchestration of Kubernetes clusters.
C. They provide isolation for datasets and Al artifacts.
D. They enhance pipeline execution speeds through workload distribution.

Answer: A,C

Explanation:
Resource groups in SAP AI Core play a vital role in managing machine learning workloads by offering mechanisms for separation and isolation, which are essential for maintaining efficiency and security.
1. Ensuring Workload Separation for Different Tenants or Departments:
* Multitenancy Support:Resource groups enable the segregation of workloads among various tenants or departments within an organization, ensuring that each unit's processes are isolated and managed independently.
* Operational Efficiency:This separation prevents interference between workloads, allowing for tailored resource allocation and management strategies that meet the specific needs of each tenant or department.

NEW QUESTION # 19
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. Joule integration in SAP SuccessFactors
C. Ready-to-use Al services
D. Open source Al model repository

Answer: A,C

NEW QUESTION # 20
How does the Al API support SAP AI scenarios? Note: There are 2 correct answers to this question.

A. By integrating Al services into business applications
B. By managing Kubernetes clusters automatically
C. By integrating Al models into third-party platforms like AWS
D. By providing a unified framework for operating Al services

Answer: A,D

Explanation:
The AI API in SAP plays a crucial role in supporting AI scenarios by facilitating the integration of AI services into business applications and providing a unified framework for operating these services.
1. Integration of AI Services into Business Applications:
* Seamless Integration:The AI API enables developers to incorporate AI functionalities directly into SAP and non-SAP business applications, enhancing their capabilities with intelligent features.
* Use Case Example:Integrating AI models into SAP Build Apps allows for the creation of AI-powered applications that can perform tasks such as data analysis, predictive modeling, and more.
2. Unified Framework for Operating AI Services:
* Standardized Operations:The AI API provides a consistent and standardized framework for managing AI services, ensuring uniformity in deployment, monitoring, and maintenance across different platforms.
* Scalability and Flexibility:This unified approach allows for scalable AI operations, accommodating various AI models and services within a cohesive operational structure.

NEW QUESTION # 21
How does SAP ensure the enterprise-readiness of its Al solutions?

A. By implementing rigorous product standards for Al capabilities
B. By ensuring that Al models make bias-free decisions without human input
C. By using generic Al models without business context complying with Al ethics standards

Answer: A

NEW QUESTION # 22
What are the applications of generative Al that go beyond traditional chatbot applications? Note: There are 2 correct answers to this question.

A. To interpret human instructions and control software systems always producing output for human consumption.
B. To interpret human instructions and control software systems without necessarily producing output for human consumption.
C. To follow a specific schema - human input, Al processing, and output for human consumption.
D. To produce outputs based on software input.

Answer: A,B

Explanation:
* C. To interpret human instructions and control software systems without necessarily producing output for human consumption.This is a key area where generative AI is breaking new ground. Think of it as AI acting as a "middleman" between you and software. Here are some examples:
* Automating complex tasks:You could tell the AI to "optimize this database for performance" or
"find and fix security vulnerabilities in this code." The AI would then interact with the software systems to carry out these instructions, without needing to show you every step or result.
* Controlling robots or IoT devices:Imagine instructing an AI to "adjust the lighting in the meeting room" or "have the robot retrieve the package from the warehouse." The AI translates your instructions into actions for those systems.
* Managing cloud resources:AI could dynamically allocate cloud resources based on your needs, scaling them up or down without your direct intervention.
* D. To interpret human instructions and control software systems always producing output for human consumption.This is more in line with traditional chatbot interactions, but with a broader scope. It's about AI generating outputs that are directly useful or informative for humans. Examples include:
* Creating realistic images or videos:Based on your description, the AI could generate a photorealistic image of a new product design or a short video clip for a marketing campaign.
* Writing different kinds of creative text formats:AI can generate stories, poems,articles, summaries, and even code, all tailored to your specifications.
* Providing personalized recommendations:AI can analyze your preferences and provide recommendations for products, services, or information.
Why the other options are incorrect:
* A. To produce outputs based on software input.This is a general capability of AI, not something specific to generative AI or beyond chatbots. Many AI systems analyze software input (like sensor data or log files) to produce outputs.
* B. To follow a specific schema - human input, AI processing, and output for human consumption.
This describes the basic interaction pattern of many AI systems, including chatbots. It's not something that specifically differentiates generative AI or goes beyond typical chatbot applications.

NEW QUESTION # 23
......

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Valid Dumps SAP C_AIG_2412 Ebook - C_AIG_2412 Latest Braindumps Sheet

SAP C_AIG_2412 Exam Syllabus Topics:

SAP C_AIG_2412 Questions Material Formats

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q18-Q23):

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