C_AIG_2412 RELIABLE TEST CRAM - REALISTIC SAP CERTIFIED ASSOCIATE - SAP GENERATIVE AI DEVELOPER OFFICIAL PRACTICE TEST FREE PDF

C_AIG_2412 Reliable Test Cram - Realistic SAP Certified Associate - SAP Generative AI Developer Official Practice Test Free PDF

C_AIG_2412 Reliable Test Cram - Realistic SAP Certified Associate - SAP Generative AI Developer Official Practice Test Free PDF

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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 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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q63-Q68):

NEW QUESTION # 63
Why is generative Al gaining significant attention and investment in the current business landscape? Note:
There are 2 correct answers to this question.

  • A. It can run entire business operations without human intervention.
  • B. It only requires natural language skills to use.
  • C. It can replicate complex technical skills without training or quality control.
  • D. It lowers barriers to adoption.

Answer: B,D

Explanation:
Generative AI is attracting significant attention and investment in the current business landscape due to several compelling factors:
1. Lowering Barriers to Adoption:
* Accessibility of Tools:The proliferation of user-friendly generative AI tools has made advanced AI capabilities accessible to a broader audience, including those without specialized technical expertise.
* Integration with Existing Systems:Generative AI solutions, such as SAP's Joule, are designed to integrate seamlessly with existing business systems, reducing the complexity and cost associated with adoption.
2. Natural Language Interaction:
* Ease of Use:Generative AI models are capable of understanding and processing natural language inputs, allowing users to interact with AI systems using everyday language. This reduces the need for specialized training and enables more intuitive user experiences.
* Enhanced User Engagement:The ability to communicate with AI systems in natural language fosters greater user engagement and facilitates the integration of AI into daily business operations.


NEW QUESTION # 64
What advantage can you gain by leveraging different models from multiple providers through the SAP's generative Al hub?

  • A. Get more training data for new models
  • B. Enhance the accuracy and relevance of Al applications that use SAP's data assets
  • C. Train new models using SAP and non-SAP data
  • D. Design new product interfaces for SAP applications

Answer: B


NEW QUESTION # 65
Which of the following capabilities does the generative Al hub provide to developers? Note: There are 2 correct answers to this question.

  • A. Code generation to extend SAP BTP applications
  • B. Tools for prompt engineering and experimentation
  • C. Integration of foundation models into applications
  • D. Proprietary LLMs exclusively

Answer: B,C

Explanation:
* C. Tools for prompt engineering and experimentation:Generative AI hubs often provide tools and resources to help developers refine their prompts. This is crucial because the quality of the output from a generative AI model heavily depends on how well the prompt is crafted. These tools might include:
* Prompt libraries:Collections of effective prompts for various tasks.
* Prompt testing and analysis:Features to test different prompts and analyze the AI's response.
* Guides and tutorials:Resources to learn about prompt engineering best practices.
* D. Integration of foundation models into applications:Generative AI hubs make it easier for developers to integrate powerful foundation models (large language models like those from Google, OpenAI, etc.) into their own applications. This means developers don't have to build these complex models from scratch. Instead, they can leverage existing models and customize them for their specific needs. This might involve:
* APIs and SDKs:Providing easy-to-use interfaces to access and interact with the foundation models.
* Model customization:Tools to fine-tune existing models on specific datasets or for particular tasks.
* Deployment options:Support for deploying AI models in different environments (cloud, on- premises, etc.).
Why the other options are incorrect:
* A. Proprietary LLMs exclusively:While some generative AI hubs might offer their own proprietary models, they usually provide access to a variety of models, including open-source and those from other providers. This gives developers more flexibility and choice.
* B. Code generation to extend SAP BTP applications:While code generation is a common feature of generative AI, it's not the primary focus of a generative AI hub. The hub's main purpose is to provide access to and facilitate the use of foundation models, not to specifically extend SAP BTP applications.


NEW QUESTION # 66
Which of the following are functionalities provided by the generative-Al-hub-SDK ? Note: There are 2 correct answers to this question.

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

Answer: A,C


NEW QUESTION # 67
What are some benefits of using an SDK for evaluating prompts within the context of generative Al?
Note: There are 3 correct answers to this question.

  • A. Maintaining data privacy by using data masking techniques
  • B. Creating custom evaluators that meet specific business needs
  • C. Supporting low code evaluations using graphical user interface
  • D. Providing metrics to quantitatively assess response quality
  • E. Automating prompt testing across various scenarios

Answer: B,D,E


NEW QUESTION # 68
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