2025 SAP REALISTIC C_AIG_2412 CERT GUIDE PASS GUARANTEED

2025 SAP Realistic C_AIG_2412 Cert Guide Pass Guaranteed

2025 SAP Realistic C_AIG_2412 Cert Guide Pass Guaranteed

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Tags: C_AIG_2412 Cert Guide, Premium C_AIG_2412 Files, Test C_AIG_2412 Voucher, Top C_AIG_2412 Exam Dumps, Reliable C_AIG_2412 Test Cram

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SAP C_AIG_2412 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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 4
  • 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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q60-Q65):

NEW QUESTION # 60
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. Providing metrics to quantitatively assess response quality
  • B. Automating prompt testing across various scenarios
  • C. Supporting low code evaluations using graphical user interface
  • D. Creating custom evaluators that meet specific business needs
  • E. Maintaining data privacy by using data masking techniques

Answer: A,B,D


NEW QUESTION # 61
Which of the following sequence of steps does SAP recommend you use to solve a business problem using generative Al hub?

  • A. Create a basic prompt in SAP AI Launchpad
    * Scale the solution using generative-ai-hub-sdk
    * Create a baseline evaluation method for the simple prompt
    * Enhance the prompts
    * Evaluate various models for the problem using generative-ai-hub-sdk
  • B. Create a basic prompt in SAP AI Launchpad
    * Enhance the prompts
    * Create a baseline evaluation method for the simple prompt
    * Evaluate various models for the problem using generative-ai-hub-sdk
    * Scale the solution using generative-ai-hub-sdk
  • C. Create a basic prompt in SAP AI Launchpad
    * Evaluate various models for the problem using generative-ai-hub-sdk
    * Scale the solution using generative-ai-hub-sdk
    * Create a baseline evaluation method for the simple prompt
    * Enhance the prompts.

Answer: B


NEW QUESTION # 62
What are some functionalities provided by SAP Al Core?
Note: There are 3 correct answers to this question.

  • A. Continuous delivery and tenant isolation for scalability
  • B. Management of SAP S/4HANA cloud infrastructure
  • C. Monitoring and retraining models in SAP Al Core
  • D. Integration of Al services with business applications using a standardized API
  • E. Orchestration of Al workflows such as model training and inference

Answer: A,D,E


NEW QUESTION # 63
Which of the following steps is NOT a requirement to use the Orchestration service?

  • A. Create a deployment for orchestration
  • B. Get an auth token for orchestration
  • C. Create an instance of an Al model
  • D. Modify the underlying Al models

Answer: D


NEW QUESTION # 64
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"])

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

Answer: D


NEW QUESTION # 65
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