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SAP C_AIG_2412 Exam Syllabus Topics:

Topic
Details

Topic 1

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.

Topic 2

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 3

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 4

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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q25-Q30):

NEW QUESTION # 25
What is a Large Language Model (LLM)?

A. A gradient boosted decision tree algorithm for predicting text.
B. An Al model that specializes in processing, understanding, and generating human language.
C. A rule-based expert system to analyze and generate grammatically correct sentences.
D. A database system optimized for storing large volumes of textual data.

Answer: B

Explanation:
A Large Language Model (LLM) is an advanced AI model designed to handle various natural language processing tasks.
1. Definition and Purpose:
* Processing:LLMs analyze human language to understand syntax, semantics, and context.
* Understanding:They interpret the meaning behind text, enabling comprehension of nuanced language elements.
* Generating:LLMs can produce coherent and contextually appropriate text, facilitating tasks like content creation and translation.
2. Characteristics of LLMs:
* Scale:These models are trained on vast datasets, encompassing billions of words, which enhances their language capabilities.
* Architecture:LLMs typically utilize complex neural network architectures, such as transformers, to manage and process language data effectively.
3. Applications:
* Content Generation:Creating articles, summaries, and reports.
* Language Translation:Converting text from one language to another with high accuracy.
* Conversational Agents:Powering chatbots and virtual assistants to interact with users naturally.

NEW QUESTION # 26
Which of the following are grounding principles included in SAP's AI Ethics framework?
Note: There are 3 correct answers to this question.

A. Human agency and oversight
B. Store all user data for legal proceedings
C. Transparency and explainability
D. Maximize business profits
E. Avoid bias and discrimination

Answer: A,C,E

NEW QUESTION # 27
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. Automatic model selection
C. Al playground and chat
D. Prompt editor and management

Answer: C,D

NEW QUESTION # 28
What are some benefits of the SAP AI Launchpad? Note: There are 2 correct answers to this question.

A. Integration with non-SAP platforms like Azure and AWS.
B. Centralized Al lifecycle management for all Al scenarios.
C. Simplified model retraining and performance improvement.
D. Direct deployment of Al models to SAP HANA.

Answer: B,C

NEW QUESTION # 29
Which statement best describes the Chain-of-Thought (COT) prompting technique?

A. Concatenating multiple related prompts to form a chain, guiding the model through sequential reasoning steps.
B. Writing a series of connected prompts creating a chain of related information.
C. Linking multiple Al models in sequence, where each model's output becomes the input for the next model in the chain.
D. Connecting related concepts by having the LLM generate chains of ideas.

Answer: A

NEW QUESTION # 30
......

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