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Vce C-AIG-2412 Download & C-AIG-2412 Valid Test Format

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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 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 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 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.

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C-AIG-2412 - SAP Certified Associate - SAP Generative AI Developer Pass-Sure Vce Download

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q13-Q18):

NEW QUESTION # 13
What is Machine Learning (ML)?

A. A technology that equips machines with human-like capabilities such as problem-solving, visual perception, and decision-making.
B. A subset of Al that focuses on enabling computer systems to learn and improve from experience or data.
C. A statistical method for data processing that does not involve any Al techniques.
D. A form of Al that only focuses on creating new content, including text, images, sound, and videos.

Answer: A,C,D

NEW QUESTION # 14
What defines SAP's approach to LLMs?

A. Ensuring ethical AI practices and seamless business integration
B. Focusing solely on reducing the computational cost of training LLMs
C. Limiting LLM usage to non-business applications only
D. Prioritizing the development of proprietary LLMs with no integration to existing systems

Answer: A

Explanation:
SAP's approach to Large Language Models (LLMs) is centered on integrating these powerful AI tools into its enterprise ecosystem while adhering to ethical standards. Unlike option A, SAP does not focus solely on proprietary LLMs without integration; instead, it leverages both proprietary and third-party models (e.g., via partnerships with providers like Azure OpenAI) to enhance business applications. Option B is incorrect because reducing computational cost is not the sole focus-SAP prioritizes value delivery through integration with business processes. Option D is also inaccurate, as SAP explicitly targets business applications rather than limiting LLMs to non-business use. Option C is correct because SAP emphasizes ethical AI practices (e.
g., through its AI Ethics Policy) and seamless integration with tools like SAP S/4HANA and SAP SuccessFactors, ensuring LLMs enhance enterprise workflows responsibly and effectively.

NEW QUESTION # 15
What are some functionalities provided by SAP Al Core?
Note: There are 3 correct answers to this question.

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

Answer: A,B,D

NEW QUESTION # 16
Which of the following is unique about SAP's approach to Al?

A. SAP's deep integration of Al with business processes and analytics.
B. Focusing Al solely on customer support services.
C. Offering Al capabilities in their future products as of 2025.
D. Utilizing Al mainly for marketing purposes.

Answer: A

Explanation:
SAP distinguishes itself by deeply embedding Artificial Intelligence (AI) into its core business processes and analytics, enhancing efficiency and decision-making across various enterprise functions.
1. Integration of AI into Business Processes:
* SAP Business AI:SAP focuses on solving customers' business problems by integrating AI directly into business processes, rather than offering general-purpose AI platforms. This approach ensures that AI solutions are tailored to specific business needs, enhancing process efficiency and effectiveness.
* SAP S/4HANA Integration:By embedding AI into SAP S/4HANA, SAP enables real-time data analysis and process optimization. This integration allows for improved supply chain efficiency, enhanced financial decision-making, and personalized customer experiences.
2. AI-Driven Analytics:
* SAP Analytics Cloud:This solution combines AI with analytics and planning, unlocking the full potential of business data. It provides advanced analytics capabilities, enabling businesses to make informed decisions based on real-time insights.
* Predictive Analytics Library:SAP HANA includes a Predictive Analytics Library with native algorithms for statistical measures, clustering, classification, and time series analysis. This facilitates advanced data processing and predictive analytics within business applications.
3. AI in Enterprise Applications:
* SAP SuccessFactors:AI is integrated into SAP SuccessFactors to enhance human resources processes, such as talent acquisition and employee engagement, by providing data-driven insights and automating routine tasks.
* SAP AI Business Services:These services offer reusable AI capabilities that can be integrated across various business processes, automating tasks like document processing andenriching customer experiences.

NEW QUESTION # 17
What are some metrics to evaluate the effectiveness of a Retrieval Augmented Generation system? Note:
There are 2 correct answers to this question.

A. Carbon footprint
B. Speed
C. Relevance
D. Faithfulness

Answer: C,D

Explanation:
Evaluating the effectiveness of a Retrieval-Augmented Generation (RAG) system involves assessing specific metrics that determine the quality and reliability of the generated content.
1. Faithfulness:
* Definition:Faithfulness measures the degree to which the generated output accurately reflects the information retrieved from source documents without introducing unsupported content.
* Importance:High faithfulness ensures that the system's responses are trustworthy and based on factual data, which is crucial for applications requiring precise information dissemination.
2. Relevance:
* Definition:Relevance assesses how pertinent the generated content is to the user's query or the task at hand.
* Importance:Ensuring relevance guarantees that the system provides information that directly addresses user needs, enhancing user satisfaction and system utility.
3. Application in RAG Systems:
* Performance Evaluation:By measuring faithfulness and relevance, developers can fine-tune RAG systems to produce outputs that are both accurate and pertinent, thereby improving overall system performance.
* User Trust:Maintaining high levels of these metrics fosters user trust, as the system consistently delivers reliable and contextually appropriate information.

NEW QUESTION # 18
......

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