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Professional C-AIG-2412 - Latest SAP Certified Associate - SAP Generative AI Developer Exam Labs

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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

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 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 4

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.

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q55-Q60):

NEW QUESTION # 55
Which of the following are functionalities provided by the generative-Al-hub-SDK ?
Note: There are 2 correct answers to this question.

A. Customize SAP AI Launchpad
B. Interact with LLMs
C. Configure SAP BTP credentials
D. Create chat responses and embeddings

Answer: B,D

NEW QUESTION # 56
What is the purpose of splitting documents into smaller overlapping chunks in a RAG system?

A. To reduce the storage space required for the vector database
B. To simplify the process of training the embedding model
C. To improve the efficiency of encoding queries into vector representations
D. To enable the matching of different relevant passages to user queries

Answer: D

NEW QUESTION # 57
Which of the following is a principle of effective prompt engineering?

A. Keep prompts as short as possible to avoid confusion.
B. Write vague and open-ended instructions to encourage creativity.
C. Use precise language and providing detailed context in prompts.
D. Combine multiple complex tasks into a single prompt.

Answer: C

Explanation:
Effective prompt engineering is crucial for guiding AI models to produce accurate and relevant outputs.
1. Importance of Precision and Context:
* Clarity:Using precise language in prompts minimizes ambiguity, ensuring the AI model comprehends the exact requirements.
* Detailed Context:Providing comprehensive context helps the model understand the background and nuances of the task, leading to more accurate and tailored responses.
2. Best Practices in Prompt Engineering:
* Specificity:Clearly define the desired outcome, including any constraints or specific formats required.
* Instruction Inclusion:Incorporate explicit instructions within the prompt to guide the model's behavior effectively.
* Avoiding Ambiguity:Steer clear of vague or open-ended language that could lead to varied interpretations.
3. Benefits of Effective Prompt Engineering:
* Enhanced Output Quality:Well-crafted prompts lead to responses that closely align with user expectations.
* Efficiency:Reduces the need for iterative refinements, saving time and computational resources.

NEW QUESTION # 58
You want to extract useful information from customer emails to augment existing applications in your company.
How can you use generative-ai-hub-sdk in this context?

A. Generate random email content and send them to customers.
B. Train custom models based on the mail data.
C. Generate JSON strings based on extracted information.
D. Generate a new SAP application based on the mail data.

Answer: C

NEW QUESTION # 59
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 integrating Al models into third-party platforms like AWS
C. By providing a unified framework for operating Al services
D. By managing Kubernetes clusters automatically

Answer: A,C

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 # 60
......

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