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[General] C-AIG-2412 Exam, Exam C-AIG-2412 Cram Review

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【General】 C-AIG-2412 Exam, Exam C-AIG-2412 Cram Review

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SAP C-AIG-2412 Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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.
Topic 2
  • 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 3
  • 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 4
  • 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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q19-Q24):NEW QUESTION # 19
Which of the following are grounding principles included in SAP's AI Ethics framework?
Note: There are 3 correct answers to this question.
  • A. Transparency and explainability
  • B. Human agency and oversight
  • C. Maximize business profits
  • D. Store all user data for legal proceedings
  • E. Avoid bias and discrimination
Answer: A,B,E

NEW QUESTION # 20
Which of the following must you do before connecting to a dataset in order to train a machine learning model in SAP Al Core?
Note: There are 2 correct answers to this question.
  • A. Grant access rights to the SAP BTP cockpit.
  • B. Store the dataset in the SAP HANA Vector Engine.
  • C. Provide the storage secret to access the dataset.
  • D. Store the dataset in a hyperscaler object store.
Answer: C,D

NEW QUESTION # 21
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. Foundation models
  • C. Rule-based algorithms
  • D. Robotic process automation
Answer: A,B
Explanation:
Generative AI encompasses technologies that create new content by learning from existing data.
1. AI Models That Generate New Content Based on Training Data:
* Definition:These models analyze large datasets to produce original outputs, such as text, images, or music, that resemble the patterns found in the training data.
* Examples:Models like GPT-4 generate human-like text, while DALL E creates images from textual descriptions.
2. Foundation Models:
* Definition:Foundation models are large-scale AI models trained on extensive data across various domains. They serve as a base for fine-tuning on specific tasks, enabling versatility in applications.
* Examples:Models such as BERT and GPT-3 are foundation models that can be adapted for tasks like translation, summarization, or content generation.

NEW QUESTION # 22
What are some features of Joule?
Note: There are 3 correct answers to this question.
  • A. Generating standalone applications.
  • B. Downloading and processing data.
  • C. Maintaining data privacy while offering generative Al capabilities.
  • D. Streamlining tasks with an Al assistant that knows your unique role.
  • E. Providing coding assistance and content generation.
Answer: C,D,E

NEW QUESTION # 23
Which of the following must you do before connecting to a dataset in order to train a machine learning model in SAP Al Core?
Note: There are 2 correct answers to this question.
  • A. Grant access rights to the SAP BTP cockpit.
  • B. Store the dataset in the SAP HANA Vector Engine.
  • C. Provide the storage secret to access the dataset.
  • D. Store the dataset in a hyperscaler object store.
Answer: C,D
Explanation:
Before connecting to a dataset for training a machine learning model in SAP AI Core, the following steps are necessary:
* Store the dataset in a hyperscaler object store:Ensure that the dataset is stored in a compatible object storage service provided by a cloud hyperscaler (e.g., AWS S3, Azure Blob Storage) to facilitate seamless access during training.
* Provide the storage secret to access the dataset:Configure the necessary access credentials (storage secrets) within SAP AI Core to securely connect to and retrieve the dataset from the object store.
These steps are essential to establish a secure and efficient connection to the dataset, enabling successful model training within SAP AI Core.

NEW QUESTION # 24
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