NEW C_AIG_2412 TEST PRICE - C_AIG_2412 TEST QUESTIONS ANSWERS

New C_AIG_2412 Test Price - C_AIG_2412 Test Questions Answers

New C_AIG_2412 Test Price - C_AIG_2412 Test Questions Answers

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q27-Q32):

NEW QUESTION # 27
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. Provide the storage secret to access the dataset.
  • B. Store the dataset in the SAP HANA Vector Engine.
  • C. Grant access rights to the SAP BTP cockpit.
  • D. Store the dataset in a hyperscaler object store.

Answer: A,D


NEW QUESTION # 28
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. Evaluate the performance of a language model using few-shot learning
  • C. Generate random examples for language model training
  • D. Train a language model from scratch

Answer: B


NEW QUESTION # 29
Which of the following are features of the SAP AI Foundation? Note: There are 2 correct answers to this question.

  • A. Joule integration in SAP SuccessFactors
  • B. Al runtimes and lifecycle management
  • C. Ready-to-use Al services
  • D. Open source Al model repository

Answer: B,C


NEW QUESTION # 30
What are the applications of generative Al that go beyond traditional chatbot applications?
Note: There are 2 correct answers to this question.

  • A. To interpret human instructions and control software systems without necessarily producing output for human consumption.
  • B. To produce outputs based on software input.
  • C. To interpret human instructions and control software systems always producing output for human consumption.
  • D. To follow a specific schema - human input, Al processing, and output for human consumption.

Answer: A,C


NEW QUESTION # 31
What does SAP recommend you do before you start training a machine learning model in SAP AI Core? Note: There are 3 correct answers to this question.

  • A. Perform manual data integration with SAP HANA.
  • B. Register the input dataset in SAP AI Core.
  • C. Define the required infrastructure resources for training.
  • D. Configure the training pipeline using templates.
  • E. Configure the model deployment in SAP Al Launchpad.

Answer: B,C,D


NEW QUESTION # 32
......

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