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Die seit kurzem aktuellsten SAP C-AIG-2412 Prüfungsinformationen, 100% Garantie für Ihen Erfolg in der Prüfungen!

Viele Leute meinen, man braucht viel fachliche IT-Kenntnisse, um die schwierigen SAP C-AIG-2412 IT-Zertifizierungsprüfung zu bestehen. Nur diejenigen, die umfassende IT-Kenntnisse besitzen, sind qualifiziert dazu, sich an der SAP C-AIG-2412 Prüfung zu beteiligen. Jetzt gibt es viele Methoden, die Ihre unausreichenden Fachkenntnisse wettmachen. Sie können sogar mit weniger Zeit und Energie als die fachlich gutqualifizierten die SAP C-AIG-2412 Prüfung auch bestehen. Wie es heißt, viele Wege führen nach Rom.

SAP C-AIG-2412 Prüfungsplan:

Thema
Einzelheiten

Thema 1

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.

Thema 2

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.

Thema 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.

Thema 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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SAP Certified Associate - SAP Generative AI Developer C-AIG-2412 Prüfungsfragen mit Lösungen (Q42-Q47):

42. Frage
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 a hyperscaler object store.
C. Provide the storage secret to access the dataset.
D. Store the dataset in the SAP HANA Vector Engine.

Antwort: B,C

Begründung:
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.

43. Frage
What is a part of LLM context optimization?

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

Antwort: B

Begründung:
LLM context optimization involves tailoring a Large Language Model's (LLM) input context to enhance its performance on specific tasks, particularly by incorporating domain-specific knowledge.
1. Understanding LLM Context Optimization:
* Definition:Context optimization refers to the process of adjusting the input provided to an LLM to ensure it includes relevant information, thereby enabling the model to generate more accurate and contextually appropriate outputs.
* Domain-Specific Knowledge Integration:By embedding domain-specific information into the model's context, the LLM can better understand and address specialized queries, leading to improved problem- solving capabilities.
2. Importance of Domain-Specific Knowledge:
* Enhanced Relevance:Providing domain-specific context ensures that the model'sresponses are pertinent to the particular field or subject matter, increasing the utility of the generated content.
* Improved Accuracy:With access to specialized knowledge, the LLLM is less likely to produce generic or incorrect answers, thereby enhancing the overall quality of its outputs.
3. Methods of Context Optimization:
* Prompt Engineering:Crafting prompts that include necessary domain-specific information to guide the model towards generating desired responses.
* Retrieval-Augmented Generation (RAG):Incorporating external data sources into the model's context to provide up-to-date and relevant information pertinent to the domain.

44. Frage
What are the benefits of SAP's generative Al hub?
Note: There are 2 correct answers to this question.

A. Build custom Al solutions and extend SAP applications
B. Accelerate Al development with flexible access to a broad range of models
C. Provide libraries for no-code development
D. Send your data to various LLM providers for training feedback

Antwort: A,B

45. Frage
Which technique is used to supply domain-specific knowledge to an LLM?

A. Retrieval-Augmented Generation
B. Fine-tuning the model on general data
C. Domain-adaptation training
D. Prompt template expansion

Antwort: C

46. Frage
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 resolving hardware malfunctions.
C. By offering generic task recommendations unrelated to specific roles.
D. By maintaining strict adherence to data privacy regulations.

Antwort: A,D

Begründung:
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.

47. Frage
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