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Oracle 1Z0-1127-25 Exam Dumps

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Description

Exam Name: Oracle Cloud Infrastructure 2025 Generative AI Professional
Exam Code: 1Z0-1127-25

Related Certification(s):

  • Oracle Cloud Certifications
  • Oracle Cloud Infrastructure Certifications
Certification Provider: Oracle
Actual Exam Duration: 90 Minutes
Number of 1Z0-1127-25 practice questions in our database: 88 

Expected 1Z0-1127-25 Exam Topics, as suggested by Oracle :

  • Module 1: Fundamentals of Large Language Models (LLMs): This section of the exam measures the skills of AI Engineers and Data Scientists in understanding the core principles of large language models. It covers LLM architectures, including transformer-based models, and explains how to design and use prompts effectively. The section also focuses on fine-tuning LLMs for specific tasks and introduces concepts related to code models, multi-modal capabilities, and language agents.
  • Module 2: Using OCI Generative AI Service: This section evaluates the expertise of Cloud AI Specialists and Solution Architects in utilizing Oracle Cloud Infrastructure (OCI) Generative AI services. It includes understanding pre-trained foundational models for chat and embedding, creating dedicated AI clusters for fine-tuning and inference, and deploying model endpoints for real-time inference. The section also explores OCI’s security architecture for generative AI and emphasizes responsible AI practices.
  • Module 3: Implement RAG Using OCI Generative AI Service: This section tests the knowledge of Knowledge Engineers and Database Specialists in implementing Retrieval-Augmented Generation (RAG) workflows using OCI Generative AI services. It covers integrating LangChain with Oracle Database 23ai, document processing techniques like chunking and embedding, storing indexed chunks in Oracle Database 23ai, performing similarity searches, and generating responses using OCI Generative AI.
  • Module 4: Using OCI Generative AI RAG Agents Service: This domain measures the skills of Conversational AI Developers and AI Application Architects in creating and managing RAG agents using OCI Generative AI services. It includes building knowledge bases, deploying agents as chatbots, and invoking deployed RAG agents for interactive use cases. The focus is on leveraging generative AI to create intelligent conversational systems.

Description

Exam Name: Oracle Cloud Infrastructure 2025 Generative AI Professional
Exam Code: 1Z0-1127-25

Related Certification(s):

  • Oracle Cloud Certifications
  • Oracle Cloud Infrastructure Certifications
Certification Provider: Oracle
Actual Exam Duration: 90 Minutes
Number of 1Z0-1127-25 practice questions in our database: 88 

Expected 1Z0-1127-25 Exam Topics, as suggested by Oracle :

  • Module 1: Fundamentals of Large Language Models (LLMs): This section of the exam measures the skills of AI Engineers and Data Scientists in understanding the core principles of large language models. It covers LLM architectures, including transformer-based models, and explains how to design and use prompts effectively. The section also focuses on fine-tuning LLMs for specific tasks and introduces concepts related to code models, multi-modal capabilities, and language agents.
  • Module 2: Using OCI Generative AI Service: This section evaluates the expertise of Cloud AI Specialists and Solution Architects in utilizing Oracle Cloud Infrastructure (OCI) Generative AI services. It includes understanding pre-trained foundational models for chat and embedding, creating dedicated AI clusters for fine-tuning and inference, and deploying model endpoints for real-time inference. The section also explores OCI’s security architecture for generative AI and emphasizes responsible AI practices.
  • Module 3: Implement RAG Using OCI Generative AI Service: This section tests the knowledge of Knowledge Engineers and Database Specialists in implementing Retrieval-Augmented Generation (RAG) workflows using OCI Generative AI services. It covers integrating LangChain with Oracle Database 23ai, document processing techniques like chunking and embedding, storing indexed chunks in Oracle Database 23ai, performing similarity searches, and generating responses using OCI Generative AI.
  • Module 4: Using OCI Generative AI RAG Agents Service: This domain measures the skills of Conversational AI Developers and AI Application Architects in creating and managing RAG agents using OCI Generative AI services. It includes building knowledge bases, deploying agents as chatbots, and invoking deployed RAG agents for interactive use cases. The focus is on leveraging generative AI to create intelligent conversational systems.

1 review for Oracle 1Z0-1127-25 Exam Dumps

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    Passed the 1Z0-1127-25 exam thanks to ExamTopics Pro. The questions were accurate and the explanations super helpful. Highly recommend for OCI Data Science prep

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Q1. What differentiates Semantic search from traditional keyword search?

A.It relies solely on matching exact keywords in the content.

B. It depends on the number of times keywords appear in the content.

C. It involves understanding the intent and context of the search.

D. It is based on the date and author of the content.

Correct Answer: C

Q2. How does the temperature setting in a decoding algorithm influence the probability distribution over the vocabulary?

A.Increasing the temperature removes the impact of the most likely word.

B. Decreasing the temperature broadens the distribution, making less likely words more probable.

C. Increasing the temperature flattens the distribution, allowing for more varied word choices.

D. Temperature has no effect on probability distribution; it only changes the speed of decoding.

Correct Answer: C

Q3. Why is it challenging to apply diffusion models to text generation?

A.Because text generation does not require complex models

B. Because text is not categorical

C. Because text representation is categorical unlike images

D. Because diffusion models can only produce images

Correct Answer: C

Q4. Given the following code: PromptTemplate(input_variables=["human_input", "city"], template=template) Which statement is true about PromptTemplate in relation to input_variables?

A.PromptTemplate requires a minimum of two variables to function properly.

B. PromptTemplate can support only a single variable at a time.

C. PromptTemplate supports any number of variables, including the possibility of having none.

D. PromptTemplate is unable to use any variables.

Correct Answer: C

Q5. What does a higher number assigned to a token signify in the "Show Likelihoods" feature of the language model token generation?

A.The token is less likely to follow the current token.

B. The token is more likely to follow the current token.

C. The token is unrelated to the current token and will not be used.

D. The token will be the only one considered in the next generation step.

Correct Answer: B

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