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SAP C-AIG-2412 Exam Syllabus Topics:

Topic
Details

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

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 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 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 (Q65-Q70):

NEW QUESTION # 65
What is a Large Language Model (LLM)?

A. A rule-based expert system to analyze and generate grammatically correct sentences.
B. An Al model that specializes in processing, understanding, and generating human language.
C. A gradient boosted decision tree algorithm for predicting text.
D. A database system optimized for storing large volumes of textual data.

Answer: B

Explanation:
A Large Language Model (LLM) is an advanced AI model designed to handle various natural language processing tasks.
1. Definition and Purpose:
* Processing:LLMs analyze human language to understand syntax, semantics, and context.
* Understanding:They interpret the meaning behind text, enabling comprehension of nuanced language elements.
* Generating:LLMs can produce coherent and contextually appropriate text, facilitating tasks like content creation and translation.
2. Characteristics of LLMs:
* Scale:These models are trained on vast datasets, encompassing billions of words, which enhances their language capabilities.
* Architecture:LLMs typically utilize complex neural network architectures, such as transformers, to manage and process language data effectively.
3. Applications:
* Content Generation:Creating articles, summaries, and reports.
* Language Translation:Converting text from one language to another with high accuracy.
* Conversational Agents:Powering chatbots and virtual assistants to interact with users naturally.

NEW QUESTION # 66
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.

A. User scripts to manually execute pipeline steps
B. Deployment templates for SAP AI Launchpad
C. Infrastructure resources such as CPUs or GPUs
D. Pipeline containers to be used

Answer: C,D

NEW QUESTION # 67
What contract type does SAP offer for Al ecosystem partner solutions?

A. Bring Your Own License (BYOL) for embedded partner solutions
B. All-in-one contracts, with services that are contracted through SAP
C. Pay-as-you-go for each partner service
D. Annual subscription-only contracts

Answer: B

Explanation:
SAP collaborates with a wide ecosystem of partners, including leading general-purpose AI vendors, to provide tailored solutions to its customers. Through the SAP Store, customers have access to numerous partner applications and a variety of tools, allowing them to choose solutions that best fit their requirements.
Contractual Approach:
* All-in-One Contracts:SAP offers all-in-one contracts for AI ecosystem partner solutions, where services are white-labeled and contracted directly through SAP. This approach simplifies the procurement process for customers, as they engage with SAP as the single point of contact for both SAP and partner services.
* Exclusion of Bring Your Own License (BYOL) Model:SAP does not adopt a "bring your own license" model for these embedded partner solutions. Instead, all services are integrated and provided under unified contracts managed by SAP.
Benefits of This Contractual Model:
* Simplified Procurement:Customers benefit from a streamlined purchasing process, dealing with a single contract and point of contact for multiple services.
* Integrated Solutions:The all-in-one contract ensures that partner solutions are seamlessly integrated with SAP's offerings, providing a cohesive experience.
* Assured Compliance and Support:By contracting through SAP, customers can be confident in the compliance, security, and support standards upheld across all services.

NEW QUESTION # 68
You want to extract useful information from customer emails to augment existing applications in your company.
How can you use generative-ai-hub-sdk in this context?

A. Generate a new SAP application based on the mail data.
B. Train custom models based on the mail data.
C. Generate JSON strings based on extracted information.
D. Generate random email content and send them to customers.

Answer: C

NEW QUESTION # 69
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. Train a language model from scratch
B. Evaluate the performance of a language model using few-shot learning
C. Generate random examples for language model training
D. Preprocess a dataset for machine learning

Answer: B

NEW QUESTION # 70
......

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Emily Fisher Emily Fisher

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