SAP C_AIG_2412 Valid Test Book - C_AIG_2412 Exam Dumps

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

NEW QUESTION # 19
What are some benefits of using an SDK for evaluating prompts within the context of generative Al?
Note: There are 3 correct answers to this question.

A. Creating custom evaluators that meet specific business needs
B. Providing metrics to quantitatively assess response quality
C. Automating prompt testing across various scenarios
D. Maintaining data privacy by using data masking techniques
E. Supporting low code evaluations using graphical user interface

Answer: A,B,C

NEW QUESTION # 20
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. Avoid bias and discrimination
C. Maximize business profits
D. Store all user data for legal proceedings
E. Human agency and oversight

Answer: A,B,E

NEW QUESTION # 21
What can be done once the training of a machine learning model has been completed in SAP AI Core? Note: There are 2 correct answers to this question.

A. The model can be deployed for inferencing.
B. The model's accuracy can be optimized directly in SAP HANA.
C. The model can be deployed in SAP HANA.
D. The model can be registered in the hyperscaler object store.

Answer: A,D

NEW QUESTION # 22
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
' --- '.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"])

A. Preprocess a dataset for machine learning
B. Train a language model from scratch
C. Evaluate the performance of a language model using few-shot learning
D. Generate random examples for language model training

Answer: C

NEW QUESTION # 23
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})

A. Define the Template and Default Input Values
B. Create the Orchestration Configuration
C. Define the LLM
D. Run the Orchestration Request

Answer: C

NEW QUESTION # 24
......

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