SAP C_AIG_2412 - SAP CERTIFIED ASSOCIATE - SAP GENERATIVE AI DEVELOPER MARVELOUS COST EFFECTIVE DUMPS

SAP C_AIG_2412 - SAP Certified Associate - SAP Generative AI Developer Marvelous Cost Effective Dumps

SAP C_AIG_2412 - SAP Certified Associate - SAP Generative AI Developer Marvelous Cost Effective Dumps

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SAP C_AIG_2412 Exam Syllabus Topics:

TopicDetails
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 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 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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q62-Q67):

NEW QUESTION # 62
Which of the following steps must be performed to deploy LLMs in the generative Al hub?

  • A. Provision SAP AI
    *Core Create a configuration
    *Run the booster
  • B. Check for foundation model scenario
    *Create a deployment
    *Configuring entitlements
  • C. Run the booster
    *Create service keys
    *Select the executable ID
  • D. Provision SAP AI Core
    *Check for foundation model scenario
    *Create a configuration
    *Create a deployment

Answer: D

Explanation:
Deploying Large Language Models (LLMs) in SAP's Generative AI Hub involves a structured process:
1. Provision SAP AI Core:
* Setup:Ensure that SAP AI Core is provisioned in your SAP Business Technology Platform (BTP) account to manage AI workloads.
2. Check for Foundation Model Scenario:
* Validation:Verify the availability of the foundation model scenario within SAP AI Core to confirm that the necessary resources and configurations are in place for deploying LLMs.
3. Create a Configuration:
* Configuration Setup:Define the parameters and settings required for the LLM deployment, including model specifications and resource allocations.
4. Create a Deployment:
* Deployment Execution:Initiate the deployment process within SAP AI Core, making the LLM available for integration and use within your applications.


NEW QUESTION # 63
Which of the following are functionalities provided by the generative-Al-hub-SDK ? Note: There are 2 correct answers to this question.

  • A. Interact with LLMs
  • B. Customize SAP AI Launchpad
  • C. Create chat responses and embeddings
  • D. Configure SAP BTP credentials

Answer: A,C

Explanation:
The Generative AI Hub SDK offers functionalities that empower developers to:
1. Interact with Large Language Models (LLMs):
* Model Access:The SDK provides a developer-friendly way to consume foundational models available in the SAP Generative AI Hub, facilitating seamless interactions with these models.
2. Create Chat Responses and Embeddings:
* Natural Language Processing:With this SDK, developers can interact with models to create natural language completions, chat responses, and embeddings, enabling the development of sophisticated AI- driven applications.
Conclusion:
The Generative AI Hub SDK enables developers to interact with LLMs and create chat responses and embeddings, supporting the development of advanced AI functionalities within applications.


NEW QUESTION # 64
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 a hyperscaler object store.
  • C. Grant access rights to the SAP BTP cockpit.
  • D. Store the dataset in the SAP HANA Vector Engine.

Answer: A,B

Explanation:
Before connecting to a dataset for training a machine learning model in SAP AI Core, the following steps are necessary:
* Store the dataset in a hyperscaler object store:Ensure that the dataset is stored in a compatible object storage service provided by a cloud hyperscaler (e.g., AWS S3, Azure Blob Storage) to facilitate seamless access during training.
* Provide the storage secret to access the dataset:Configure the necessary access credentials (storage secrets) within SAP AI Core to securely connect to and retrieve the dataset from the object store.
These steps are essential to establish a secure and efficient connection to the dataset, enabling successful model training within SAP AI Core.


NEW QUESTION # 65
Why is generative Al gaining significant attention and investment in the current business landscape? Note:
There are 2 correct answers to this question.

  • A. It lowers barriers to adoption.
  • B. It only requires natural language skills to use.
  • C. It can run entire business operations without human intervention.
  • D. It can replicate complex technical skills without training or quality control.

Answer: A,B

Explanation:
Generative AI is attracting significant attention and investment in the current business landscape due to several compelling factors:
1. Lowering Barriers to Adoption:
* Accessibility of Tools:The proliferation of user-friendly generative AI tools has made advanced AI capabilities accessible to a broader audience, including those without specialized technical expertise.
* Integration with Existing Systems:Generative AI solutions, such as SAP's Joule, are designed to integrate seamlessly with existing business systems, reducing the complexity and cost associated with adoption.
2. Natural Language Interaction:
* Ease of Use:Generative AI models are capable of understanding and processing natural language inputs, allowing users to interact with AI systems using everyday language. This reduces the need for specialized training and enables more intuitive user experiences.
* Enhanced User Engagement:The ability to communicate with AI systems in natural language fosters greater user engagement and facilitates the integration of AI into daily business operations.


NEW QUESTION # 66
Which of the following capabilities does the generative Al hub provide to developers? Note: There are 2 correct answers to this question.

  • A. Code generation to extend SAP BTP applications
  • B. Integration of foundation models into applications
  • C. Tools for prompt engineering and experimentation
  • D. Proprietary LLMs exclusively

Answer: B,C

Explanation:
* C. Tools for prompt engineering and experimentation:Generative AI hubs often provide tools and resources to help developers refine their prompts. This is crucial because the quality of the output from a generative AI model heavily depends on how well the prompt is crafted. These tools might include:
* Prompt libraries:Collections of effective prompts for various tasks.
* Prompt testing and analysis:Features to test different prompts and analyze the AI's response.
* Guides and tutorials:Resources to learn about prompt engineering best practices.
* D. Integration of foundation models into applications:Generative AI hubs make it easier for developers to integrate powerful foundation models (large language models like those from Google, OpenAI, etc.) into their own applications. This means developers don't have to build these complex models from scratch. Instead, they can leverage existing models and customize them for their specific needs. This might involve:
* APIs and SDKs:Providing easy-to-use interfaces to access and interact with the foundation models.
* Model customization:Tools to fine-tune existing models on specific datasets or for particular tasks.
* Deployment options:Support for deploying AI models in different environments (cloud, on- premises, etc.).
Why the other options are incorrect:
* A. Proprietary LLMs exclusively:While some generative AI hubs might offer their own proprietary models, they usually provide access to a variety of models, including open-source and those from other providers. This gives developers more flexibility and choice.
* B. Code generation to extend SAP BTP applications:While code generation is a common feature of generative AI, it's not the primary focus of a generative AI hub. The hub's main purpose is to provide access to and facilitate the use of foundation models, not to specifically extend SAP BTP applications.


NEW QUESTION # 67
......

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