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SAP C_AIG_2412 Exam Syllabus Topics:
Topic
Details
Topic 1
- 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 2
- 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 3
- 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 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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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q25-Q30):
NEW QUESTION # 25
What are some drivers for the rapid adoption of generative AI? Note: There are 2 correct answers to this question.
- A. Wide availability
- B. Availability of skilled developers
- C. Significant hardware cost savings
- D. Ease of use
Answer: A,D
NEW QUESTION # 26
How does SAP deal with vulnerability risks created by generative Al? Note: There are 2 correct answers to this question.
- A. By identifying human, technical, and exfiltration risks through an Al Security Taskforce.
- B. By implementing responsible Al use guidelines and strong product security standards.
- C. By focusing on technological advancement only.
- D. By relying on external vendors to manage security threats.
Answer: A,B
NEW QUESTION # 27
What are some functionalities provided by SAP Al Core? Note: There are 3 correct answers to this question.
- A. Monitoring and retraining models in SAP Al Core
- B. Continuous delivery and tenant isolation for scalability
- C. Integration of Al services with business applications using a standardized API
- D. Management of SAP S/4HANA cloud infrastructure
- E. Orchestration of Al workflows such as model training and inference
Answer: B,C,E
Explanation:
You're asking about the key functionalities of SAP AI Core. Here's a breakdown of the correct answers:
* A. Integration of AI services with business applications using a standardized API:SAP AI Core provides a standardized way to connect AI models and services to your existing business applications.
This means you can easily integrate AI capabilities into your core business processes, regardless of the specific AI technology you're using. This is done through APIs (Application Programming Interfaces), which allow different software systems to communicate with each other.
* B. Continuous delivery and tenant isolation for scalability:
* Continuous delivery:AI Core supports continuous delivery, which means you can quickly and easily deploy and update your AI models. This allows you to adapt to changing business needs and keep your AI solutions up-to-date.
* Tenant isolation:AI Core provides tenant isolation, which is important for security and scalability. This means that different users or departments within your organization can have their own separate AI environments, preventing interference and ensuring data privacy.
* C. Orchestration of AI workflows such as model training and inference:AI Core helps you manage the entire lifecycle of your AI models, including:
* Training:Automating the process of training your AI models on large datasets.
* Inference:Deploying your trained models and using them to make predictions or generate insights.
* Monitoring:Tracking the performance of your AI models over time.
Why the other options are incorrect:
* D. Management of SAP S/4HANA cloud infrastructure:While AI Core can be used with S/4HANA, it's not specifically designed to manage the cloud infrastructure of S/4HANA. That's handled by other SAP services.
* E. Monitoring and retraining models in SAP AI Core:While AI Core supports monitoring, the retraining of models is typically done using other tools and services within the SAP AI ecosystem.
NEW QUESTION # 28
What are the benefits of SAP's generative Al hub? Note: There are 2 correct answers to this question.
- A. Send your data to various LLM providers for training feedback
- B. Accelerate Al development with flexible access to a broad range of models
- C. Provide libraries for no-code development
- D. Build custom Al solutions and extend SAP applications
Answer: B,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 # 29
What are some advantages of using agents in training models? Note: There are 2 correct answers to this question.
- A. To eliminate the need for human oversight
- B. To improve the quality of results
- C. To streamline LLM workflows
- D. To guarantee accurate decision making in complex scenarios
Answer: B,C
NEW QUESTION # 30
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