EXAM DUMPS C-AIG-2412 ZIP - C-AIG-2412 NEW STUDY NOTES

Exam Dumps C-AIG-2412 Zip - C-AIG-2412 New Study Notes

Exam Dumps C-AIG-2412 Zip - C-AIG-2412 New Study Notes

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SAP C-AIG-2412 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 (Q23-Q28):

NEW QUESTION # 23
Which of the following executables in generative Al hub works with Anthropic models?

  • A. GCP Vertex Al
  • B. SAP AI Core
  • C. AWS Bedrock
  • D. Azure OpenAl Service

Answer: C

Explanation:
In SAP's Generative AI Hub, the integration with Anthropic models is facilitated through specific executables:
1. AWS Bedrock:
* Integration with Anthropic Models:AWS Bedrock provides access to Anthropic's Claude models, enabling developers to utilize these models within their applications.
* Execution via Generative AI Hub:Through the Generative AI Hub, developers can select AWS Bedrock as the executable to work with Anthropic models, integrating them into their AI solutions.
Conclusion:
To work with Anthropic models within SAP's Generative AI Hub, developers should utilize the AWS Bedrock executable, which provides access to these models for integration into their applications.


NEW QUESTION # 24
What is a part of LLM context optimization?

  • A. Providing the model with domain-specific knowledge needed to solve a problem
  • B. Reducing the model's size to improve efficiency
  • C. Enhancing the computational speed of the model
  • D. Adjusting the model's output format and style

Answer: A

Explanation:
LLM context optimization involves tailoring a Large Language Model's (LLM) input context to enhance its performance on specific tasks, particularly by incorporating domain-specific knowledge.
1. Understanding LLM Context Optimization:
* Definition:Context optimization refers to the process of adjusting the input provided to an LLM to ensure it includes relevant information, thereby enabling the model to generate more accurate and contextually appropriate outputs.
* Domain-Specific Knowledge Integration:By embedding domain-specific information into the model's context, the LLM can better understand and address specialized queries, leading to improved problem- solving capabilities.
2. Importance of Domain-Specific Knowledge:
* Enhanced Relevance:Providing domain-specific context ensures that the model'sresponses are pertinent to the particular field or subject matter, increasing the utility of the generated content.
* Improved Accuracy:With access to specialized knowledge, the LLLM is less likely to produce generic or incorrect answers, thereby enhancing the overall quality of its outputs.
3. Methods of Context Optimization:
* Prompt Engineering:Crafting prompts that include necessary domain-specific information to guide the model towards generating desired responses.
* Retrieval-Augmented Generation (RAG):Incorporating external data sources into the model's context to provide up-to-date and relevant information pertinent to the domain.


NEW QUESTION # 25
How does the Al API support SAP AI scenarios? Note: There are 2 correct answers to this question.

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

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 # 26
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. Combine multiple complex tasks into a single prompt.
  • D. Use precise language and providing detailed context in prompts.

Answer: D

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 # 27
How does SAP ensure the enterprise-readiness of its Al solutions?

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

Answer: C

Explanation:
SAP ensures the enterprise-readiness of its AI solutions through the implementation of rigorous product standards:
1. Rigorous Product Standards for AI Capabilities:
* Development Guidelines:SAP adheres to strict guidelines during the development of AI systems, ensuring they meet high standards of quality, security, and performance.
* Ethical Framework:SAP's AI Ethics Policy governs the development, deployment, use, and sale of AI systems, defining clear ethical rules aligned with global standards.
* Compliance and Governance:SAP has established governance bodies and processes to oversee AI ethics, ensuring that AI solutions are developed and deployed responsibly.


NEW QUESTION # 28
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