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SAP C_AIG_2412 Exam Course - Test C_AIG_2412 Passing Score

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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 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.

Topic 4

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.

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Test C_AIG_2412 Passing Score - C_AIG_2412 Exam Questions Pdf

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q19-Q24):

NEW QUESTION # 19
What are some metrics to evaluate the effectiveness of a Retrieval Augmented Generation system?
Note: There are 2 correct answers to this question.

A. Speed
B. Carbon footprint
C. Relevance
D. Faithfulness

Answer: C,D

NEW QUESTION # 20
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. Pipeline containers to be used
C. Deployment templates for SAP AI Launchpad
D. User scripts to manually execute pipeline steps

Answer: A,B

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 # 21
What capabilities does the Exploration and Development feature of the generative Al hub provide?
Note: There are 2 correct answers to this question.

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

Answer: A,C

NEW QUESTION # 22
What advantage can you gain by leveraging different models from multiple providers through the SAP's generative Al hub?

A. Get more training data for new models
B. Design new product interfaces for SAP applications
C. Train new models using SAP and non-SAP data
D. Enhance the accuracy and relevance of Al applications that use SAP's data assets

Answer: D

NEW QUESTION # 23
How can Joule improve workforce productivity? Note: There are 2 correct answers to this question.

A. By providing context-based role-specific task assistance.
B. By offering generic task recommendations unrelated to specific roles.
C. By maintaining strict adherence to data privacy regulations.
D. By resolving hardware malfunctions.

Answer: A,C

Explanation:
SAP's AI copilot, Joule, enhances workforce productivity through several key features:
1. Adherence to Data Privacy Regulations:
* Data Security and Privacy:Joule is designed with a strong emphasis on data security and privacy, ensuring compliance with data protection regulations. This adherence builds user trust and allows employees to utilize AI tools confidently, knowing that their data is handled responsibly.
2. Context-Based Role-Specific Task Assistance:
* Personalized Assistance:Joule provides context-aware support tailored to individual roles within an organization. By understanding the specific needs and responsibilities of each user, Joule offers relevant insights and automates routine tasks, thereby enhancing efficiency and allowing employees to focus on higher-value activities.

NEW QUESTION # 24
......

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