Updated Free SAP C_AIG_2412 Test Engine Questions with 66 Q&As [Q29-Q44]

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Updated Free SAP C_AIG_2412 Test Engine Questions with 66 Q&As

The Best SAP Certified Associate C_AIG_2412 Professional Exam Questions

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	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 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	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.

NO.29 You want to use the orchestration service through SAP’s generative-Al-hub-sdk. What does the following code do?
from gen_ai_hub.orchestration.models.11m import LLM 11m =
LLM(name=”gpt-40″, version=”latest”, parameters={“max_tokens”: 256, “temperature”: 0.2})

Define the LLM

Run the Orchestration Request

Create the Orchestration Configuration

Define the Template and Default Input Values

NO.30 You want to use the orchestration service through SAP’s generative-Al-hub-sdk. What does the following code do?
from gen_ai_hub.orchestration.models.11m import LLM 11m =
LLM(name=”gpt-40″, version=”latest”, parameters={“max_tokens”: 256, “temperature”: 0.2})

Define the LLM

Run the Orchestration Request

Create the Orchestration Configuration

Define the Template and Default Input Values

NO.31 Which of the following describes Large Language Models (LLMs)?

They rely on traditional rule-based algorithms to generate responses

They utilize deep learning to process and generate human-like text

They can only process numerical data and are not capable of understanding text

They generate responses based on pre-defined templates without learning from data

NO.32 What are some components of the training pipeline in SAP AI Core?
Note: There are 2 correct answers to this question.

Input datasets stored in a hyperscaler object store

Executables that define the training process

The SAP HANA database for model storage

Automated deployment to Kubernetes clusters

NO.33 What are some characteristics of the SAP generative Al hub? Note: There are 2 correct answers to this question.

It operates independently of SAP’s partners and ecosystem.

It ensures relevant, reliable, and responsible business Al.

It only supports traditional machine learning models.

It provides instant access to a wide range of large language models (LLMs).

NO.34 You want to assign urgency and sentiment categories to a large number of customer emails. You want to get a valid json string output for creating custom applications. You decide to develop a prompt for the same using generative Al hub.
What is the main purpose of the following code in this context?
prompt_test = “””Your task is to extract and categorize messages. Here are some examples:
{{?technique_examples}}
Use the examples when extract and categorize the following message:
{{?input}}
Extract and return a json with the following keys and values:
-“urgency” as one of {{?urgency}}
-“sentiment” as one of {{?sentiment}}
“categories” list of the best matching support category tags from: {{?categories}} Your complete message should be a valid json string that can be read directly and only contains the keys mentioned in t import random random.seed(42) k = 3 examples random. sample (dev_set, k) example_template = “””<example> {example_input} examples
‘n—n’.join([example_template.format(example_input=example [“message”], example_output=json.dumps (example[ f_test = partial (send_request, prompt=prompt_test, technique_examples examples, **option_lists) response = f_test(input=mail[“message”])

Generate random examples for language model training

Evaluate the performance of a language model using few-shot learning

Train a language model from scratch

Preprocess a dataset for machine learning

NO.35 How does SAP deal with vulnerability risks created by generative Al?
Note: There are 2 correct answers to this question.

By implementing responsible Al use guidelines and strong product security standards.

By identifying human, technical, and exfiltration risks through an Al Security Taskforce.

By focusing on technological advancement only.

By relying on external vendors to manage security threats.

NO.36 Which of the following are features of the SAP AI Foundation? Note: There are 2 correct answers to this question.

Ready-to-use Al services

Al runtimes and lifecycle management

Open source Al model repository

Joule integration in SAP SuccessFactors

NO.37 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.

Pipeline containers to be used

Infrastructure resources such as CPUs or GPUs

User scripts to manually execute pipeline steps

Deployment templates for SAP AI Launchpad

NO.38 Which of the following are functionalities provided by the generative-Al-hub-SDK ? Note: There are 2 correct answers to this question.

Interact with LLMs

Configure SAP BTP credentials

Customize SAP AI Launchpad

Create chat responses and embeddings

NO.39 What are some examples of generative Al technologies? Note: There are 2 correct answers to this question.

Al models that generate new content based on training data

Rule-based algorithms

Robotic process automation

Foundation models

NO.40 Which neural network architecture is primarily used by LLMs?

Transformer architecture with self-attention mechanisms

Recurrent neural network architecture

Convolutional Neural Networks (CNNs)

Sequential encoder-decoder architecture

NO.41 Which technique is used to supply domain-specific knowledge to an LLM?

Domain-adaptation training

Prompt template expansion

Retrieval-Augmented Generation

Fine-tuning the model on general data

NO.42 Which statement best describes the Chain-of-Thought (COT) prompting technique?

Linking multiple Al models in sequence, where each model’s output becomes the input for the next model in the chain.

Writing a series of connected prompts creating a chain of related information.

Concatenating multiple related prompts to form a chain, guiding the model through sequential reasoning steps.

Connecting related concepts by having the LLM generate chains of ideas.

NO.43 What are the benefits of SAP’s generative Al hub? Note: There are 2 correct answers to this question.

Accelerate Al development with flexible access to a broad range of models

Provide libraries for no-code development

Build custom Al solutions and extend SAP applications

Send your data to various LLM providers for training feedback

NO.44 What is a significant risk associated with using LLMs?

Complete elimination of human oversight in content creation

Inability to generate text in multiple languages

Potential biases in generated content

Unlimited processing power usage without cost control

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Updated Free SAP C_AIG_2412 Test Engine Questions with 66 Q&As [Q29-Q44]

SAP C_AIG_2412 Exam Syllabus Topics:

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