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2025 SAP C_AIG_2412: Accurate Exam SAP Certified Associate - SAP Generative AI Developer Fee

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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

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'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

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 (Q49-Q54):

NEW QUESTION # 49
How can few-shot learning enhance LLM performance?

A. By enhancing the model's computational efficiency
B. By providing a large training set to improve generalization
C. By reducing overfitting through regularization techniques
D. By offering input-output pairs that exemplify the desired behavior

Answer: D

NEW QUESTION # 50
Which of the following are features of the SAP AI Foundation? Note: There are 2 correct answers to this question.

A. Open source Al model repository
B. Al runtimes and lifecycle management
C. Joule integration in SAP SuccessFactors
D. Ready-to-use Al services

Answer: B,D

Explanation:
SAP AI Foundation is an all-in-one AI toolkit that provides developers with the necessary tools to build AI- powered extensions and applications on SAP Business Technology Platform (SAP BTP).
1. Ready-to-Use AI Services:
* Pre-Built AI Capabilities:AI Foundation offers a suite of ready-to-use AI services, enabling developers to integrate AI functionalities into their applications without the need to build models from scratch. These services include capabilities such as document information extraction, translation, and personalized recommendations.
2. AI Runtimes and Lifecycle Management:
* Comprehensive AI Management:AI Foundation provides tools for managing AI runtimes and the entire AI lifecycle, including model deployment, monitoring, and maintenance. This ensures that AI models operate efficiently and remain up-to-date, facilitating seamless integration into business processes.
3. Integration with SAP BTP:
* Unified Platform:By integrating with SAP BTP, AI Foundation allows for the development of AI solutions that are grounded in business data and context, ensuring relevance and reliability in AI-driven applications.

NEW QUESTION # 51
Which of the following is a benefit of using Retrieval Augmented Generation?

A. It eliminates the need for fine-tuning LLMs for specific tasks.
B. It allows LLMs to access and utilize information beyond their initial training data.
C. It reduces the computational resources required for language modeling.
D. It enables LLMs to learn new languages without additional training.

Answer: B

Explanation:
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by enabling them to access and utilize information beyond their initial training data.
1. Understanding Retrieval-Augmented Generation (RAG):
* Definition:RAG combines the generative capabilities of LLMs with retrieval mechanisms that access external knowledge bases or documents. This integration allows the model to incorporate up-to-date and domain-specific information into its responses.
* Mechanism:When presented with a query, the RAG system retrieves pertinent information from external sources and uses this data to inform and generate a more accurate and contextually appropriate response.
2. Benefits of RAG:
* Access to External Information:RAG allows LLMs to access and utilize information beyond their initial training data, enabling them to provide more accurate and relevant responses.
* Up-to-Date Information:Since RAG systems can query current data sources, they are capable of providing the most recent information available, which is crucial in dynamic fields.
* Improved Accuracy and Relevance:By leveraging external data, RAG enhances theaccuracy and relevance of the generated content, making it particularly useful for tasks requiring detailed or domain- specific information.

NEW QUESTION # 52
What must be defined in an executable to train a machine learning model using SAP AI Core? Note: There are 2 correct answers to this question.

A. Infrastructure resources such as CPUs or GPUs
B. User scripts to manually execute pipeline steps
C. Pipeline containers to be used
D. Deployment templates for SAP AI Launchpad

Answer: A,C

Explanation:
When training a machine learning model using SAP AI Core, defining an executable requires specifying certain key components to ensure the training process is efficient and effective.
1. Pipeline Containers to Be Used:
* Definition:Pipeline containers encapsulate the environments and dependencies necessary for each step of the machine learning workflow, including data preprocessing, model training, and evaluation.
* Specification in Executable:Within the executable, it's essential to define which pipeline containers will be utilized to ensure that each stage of the training process has the appropriate tools and libraries.

NEW QUESTION # 53
What must be defined in an executable to train a machine learning model using SAP AI Core? Note:
There are 2 correct answers to this question.

A. Infrastructure resources such as CPUs or GPUs
B. User scripts to manually execute pipeline steps
C. Pipeline containers to be used
D. Deployment templates for SAP AI Launchpad

Answer: A,C

NEW QUESTION # 54
......

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