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Oracle Cloud Infrastructure 2024 Generative AI Professional (1Z0-1127-24)

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Oracle Cloud Infrastructure 2024 Generative AI Professional (1Z0-1127-24) 


The Oracle Cloud Infrastructure 2024 Generative AI Professional certification is designed for Software Developers, Machine Learning/AI Engineers, and Generative AI Professionals who have a foundational understanding of Machine Learning and Deep Learning concepts, along with familiarity with Python and Oracle Cloud Infrastructure (OCI).


Exam Objectives

The Oracle Cloud Infrastructure 2024 Generative AI Professional (1Z0-1127-24) Exam covers the following topics - 

  • Module 1 - Explain Fundamentals of Large Language Models (LLMs) - 20%
  • Module 2 - Learn about Using OCI Generative AI Service - 45%
  • Module 3 - Learn about Building an LLM Application with OCI Generative AI Service - 35%

Oracle Cloud Infrastructure 2024 Generative AI Professional (1Z0-1127-24) FAQs

The exam is in a multiple-choice format and has a duration of 90 minutes.

The exam consists of 40 questions, and the passing score is 65%.

The certification is designed for Software Developers, Machine Learning/AI Engineers, and Generative AI Professionals with a basic understanding of Machine Learning and Deep Learning concepts, and familiarity with Python and Oracle Cloud Infrastructure.

Certified professionals will have a strong understanding of Large Language Model (LLM) architecture and be skilled in using OCI Generative AI Services, such as Retrieval-Augmented Generation (RAG) and LangChain, to build, trace, evaluate, and deploy LLM applications.

The main topics are:

  • Fundamentals of Large Language Models (LLMs) (20%)
  • Using OCI Generative AI Service (45%)
  • Building an LLM Application with OCI Generative AI Service (35%)

The purchased exam must be redeemed within six months.

Hands-on experience with OCI services through labs and/or fieldwork is recommended, which can be gained via Oracle training and learning subscriptions.

The exam covers the OCI Generative AI security architecture, ensuring that AI models and data meet security and compliance standards.