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Get Certified on the First Attempt with SAP C_AIG_2412 Exam Dumps

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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

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 3

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 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 (Q19-Q24):

NEW QUESTION # 19
What are some examples of generative Al technologies?
Note: There are 2 correct answers to this question.

A. Al models that generate new content based on training data
B. Robotic process automation
C. Rule-based algorithms
D. Foundation models

Answer: A,D

NEW QUESTION # 20
What capabilities does the Exploration and Development feature of the generative Al hub provide? Note: There are 2 correct answers to this question.

A. Develop and debug ABAP code
B. Al playground and chat
C. Automatic model selection
D. Prompt editor and management

Answer: B,D

NEW QUESTION # 21
What is a part of LLM context optimization?

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

Answer: D

NEW QUESTION # 22
What contract type does SAP offer for Al ecosystem partner solutions?

A. Bring Your Own License (BYOL) for embedded partner solutions
B. Annual subscription-only contracts
C. All-in-one contracts, with services that are contracted through SAP
D. Pay-as-you-go for each partner service

Answer: B,C,D

NEW QUESTION # 23
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. Creating custom evaluators that meet specific business needs
B. Maintaining data privacy by using data masking techniques
C. Providing metrics to quantitatively assess response quality
D. Supporting low code evaluations using graphical user interface
E. Automating prompt testing across various scenarios

Answer: A,C,E

Explanation:
Utilizing an SDK for evaluating prompts within the context of generative AI offers several benefits:
1. Creating Custom Evaluators That Meet Specific Business Needs:
* Tailored Evaluation Metrics:An SDK allows developers to design and implement custom evaluation metrics that align with specific business objectives, ensuring that prompt assessments are relevant and meaningful.
* Flexibility in Evaluation Criteria:Developers can define criteria that reflect the unique requirements of their applications, leading to more accurate and business-aligned evaluations.
2. Automating Prompt Testing Across Various Scenarios:
* Scalability:An SDK enables the automation of prompt testing across multiple scenarios, facilitating large-scale evaluations without manual intervention.
* Consistency:Automated testing ensures consistent application of evaluation criteria, reducing the potential for human error and increasing reliability.
3. Providing Metrics to Quantitatively Assess Response Quality:
* Objective Assessment:The SDK can generate quantitative metrics, such as accuracy, relevance, and coherence scores, providing an objective basis for evaluating prompt performance.
* Performance Monitoring:These metrics enable continuous monitoring and improvement of prompt quality, ensuring that AI models deliver optimal results.

NEW QUESTION # 24
......

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