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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 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 2
- 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 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 (Q14-Q19):
NEW QUESTION # 14
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 only requires natural language skills to use.
- B. It lowers barriers to adoption.
- C. It can replicate complex technical skills without training or quality control.
- D. It can run entire business operations without human intervention.
Answer: A,B
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 # 15
What are some metrics to evaluate the effectiveness of a Retrieval Augmented Generation system? Note: There are 2 correct answers to this question.
- A. Relevance
- B. Speed
- C. Faithfulness
- D. Carbon footprint
Answer: A,C
NEW QUESTION # 16
What is the primary function of the generative Al hub in SAP's Al Foundation?
- A. To provide ready-to-use Al services for document processing
- B. To manage the Al lifecycle efforts end-to-end
- C. To store embeddings of unstructured data for semantic data retrieval
- D. To serve as an abstraction layer to access a range of foundation Al models
Answer: D
Explanation:
SAP's Generative AI Hub, a component of the SAP AI Foundation, provides a unified platform for accessing various foundation AI models.
1. Abstraction Layer Functionality:
* Unified Access:The Generative AI Hub acts as an abstraction layer, offering developers seamless access to a diverse range of large language models (LLMs) from multiple providers, such as GPT-4 by Azure OpenAI and open-source models like Falcon-40b.
* Simplified Integration:By providing a standardized interface, the hub simplifies the integration of these models into applications, reducing complexity and development time.
2. Supporting AI Development:
* Toolset Availability:The hub offers a comprehensive toolset for building custom AI solutions, including prompt engineering tools, SDKs, and fine-tuning services, facilitating efficient AI development.
* Model Orchestration:Developers can orchestrate multiple models, enabling the selection of the most suitable model for specific use cases, thereby enhancing the accuracy and relevance of AI applications.
NEW QUESTION # 17
Which of the following steps is NOT a requirement to use the Orchestration service?
- A. Create an instance of an Al model
- B. Modify the underlying Al models
- C. Create a deployment for orchestration
- D. Get an auth token for orchestration
Answer: B
Explanation:
To utilize the Orchestration service in SAP's Generative AI Hub, several steps are required; however, modifying the underlying AI models is not among them:
1. Required Steps:
* Get an Auth Token for Orchestration:Obtain authentication credentials to access the orchestration service.
* Create an Instance of an AI Model:Set up an instance of the desired AI model to be used within the orchestration pipeline.
* Create a Deployment for Orchestration:Deploy the configured AI model instance to the orchestration service, enabling it for processing requests.
2. Not Required:
* Modify the Underlying AI Models:The orchestration service allows users to utilize pre-existing AI models without the need to alter their foundational architecture or training.
NEW QUESTION # 18
What are the benefits of SAP's generative Al hub? Note: There are 2 correct answers to this question.
- A. Provide libraries for no-code development
- B. Send your data to various LLM providers for training feedback
- C. Build custom Al solutions and extend SAP applications
- D. Accelerate Al development with flexible access to a broad range of models
Answer: C,D
Explanation:
SAP's Generative AI Hub offers several benefits that enhance AI development and integration within business processes:
1. Accelerate AI Development with Flexible Access to a Broad Range of Models:
* Diverse Model Access:The Generative AI Hub provides instant access to a wide array of large language models (LLMs) from various providers, such as GPT-4 by Azure OpenAI and open-source models like Falcon-40b.
* Flexible Integration:This access allows developers to select and utilize the most suitable models for their specific use cases, thereby accelerating AI development and deployment.
2. Build Custom AI Solutions and Extend SAP Applications:
* Custom AI Solutions:The hub offers a comprehensive toolset for building custom AI solutions, including prompt engineering tools, SDKs, and fine-tuning services.
* Extending SAP Applications:Developers can leverage these tools to create AI-powered extensions for SAP applications like SAP S/4HANA and SAP SuccessFactors, enhancing their functionality and adaptability.
NEW QUESTION # 19
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