Study with Oracle : 1z0-1127-24 Exam Torrent as your best preparation materials
Last Updated: Sep 21, 2026
No. of Questions: 66 Questions & Answers with Testing Engine
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A well-organized layout is an underrated study tool. The 1z0-1127-24 exam materials at SurePassExams group 66 practice questions around the Oracle Cloud Infrastructure 2024 Generative AI Professional objectives in a structure that makes key points easy to find, easy to review, and easy to remember — because time saved on hunting is time spent on learning.
Oracle 1z0-1127-24 Exam Overview:
| Certification Vendor: | Oracle |
|---|---|
| Exam Name: | Oracle Cloud Infrastructure 2024 Generative AI Professional |
| Exam Number: | 1Z0-1127-24 |
| Exam Duration: | 90 minutes |
| Available Languages: | English |
| Exam Price: | $245 USD |
| Related Certifications: | Oracle Cloud Infrastructure Certified AI Professional |
| Exam Format: | Multiple Select, Multiple Choice |
| Passing Score: | 68% |
| Real Exam Qty: | 60 |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored or in-person testing center |
| Pre Condition: | Recommended: Basic knowledge of cloud computing concepts, familiarity with AI/ML fundamentals, and understanding of Oracle Cloud Infrastructure |
| Official Syllabus URL: | https://education.oracle.com/oracle-cloud-infrastructure-2024-generative-ai-professional |
Oracle 1z0-1127-24 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Oracle Cloud Infrastructure (OCI) Generative AI Service | 25% | - Security and access control in OCI Gen AI - API usage and integration patterns - Pricing and resource management - Available models and model selection - OCI Generative AI service architecture - Service deployment and configuration |
| Prompt Engineering | 20% | - Prompt templates and patterns - Iterative prompt refinement - Chain of thought prompting - Prompt design principles and best practices - Prompt optimization for specific tasks - Few-shot and zero-shot prompting techniques |
| OCI AI Services Integration | 10% | - Multi-modal AI capabilities - Integration with OCI Language - End-to-end solution architecture - Integration with OCI Vision |
| Retrieval Augmented Generation (RAG) | 20% | - Document chunking strategies - Vector databases and embeddings - Retrieval optimization techniques - RAG architecture and components - Implementing RAG on OCI - Evaluation metrics for RAG systems |
| Introduction to Generative AI | 15% | - Key terminology and vocabulary - Generative AI concepts and definitions - Business applications and use cases - Key components of generative AI systems - History and evolution of generative AI models |
| Fine-tuning and Model Customization | 10% | - Fine-tuning concepts and approaches - Model evaluation and validation - Training data preparation - Hyperparameter tuning - Fine-tuning with OCI tools |
1z0-1127-24 Exam FAQ: Study Smarter, Not Longer
Recommended: Basic knowledge of cloud computing concepts, familiarity with AI/ML fundamentals, and understanding of Oracle Cloud Infrastructure
The 1z0-1127-24 exam contains 60 questions with 90 minutes minutes on the clock. That combination rewards candidates who have rehearsed under realistic conditions — which is exactly what the software simulation version of the SurePassExams materials is for.
The official outline divides the 1z0-1127-24 exam into weighted domains, including:
- Retrieval Augmented Generation (RAG) (20%)
- Fine-tuning and Model Customization (10%)
- Prompt Engineering (20%)
The Oracle Cloud Infrastructure 2024 Generative AI Professional question bank at SurePassExams is organized around these same objectives, and its clear layout makes the heavily weighted points easy to spot and revisit.
The passing score is 68% and the exam fee is $245 USD. A practical approach: keep running timed practice sets until your results sit comfortably above the passing line, then book your seat.
Because knowing the content and knowing the exam are different skills. The software version of the Oracle Cloud Infrastructure 2024 Generative AI Professional materials simulates the real 1z0-1127-24 exam environment, so the interface, timing, and question flow are familiar before you sit the real thing. It is a small rehearsal with an outsized effect — candidates who have experienced the simulation handle exam-day details calmly instead of burning time on surprises.
The 1z0-1127-24 exam is the official test for the Oracle Cloud Infrastructure 2024 Generative AI Professional certification from Oracle, measuring how well you can apply the published exam objectives in realistic scenarios. The credential validates your skills against an industry-recognized standard — and because the exam has its own format and rhythm, materials that combine organized content with realistic simulation prepare you more completely than reading alone.
Three things. First, it starts with a free demo containing plenty of sample questions, so you can taste the 1z0-1127-24 exam content before deciding. Second, the PDF prints cleanly, turning your screen materials into paper you can annotate — notes in the margins keep your memory of key points fresh every time you pick the pages back up. Third, it travels anywhere: no account login, no compatibility worries, just 66 practice questions for the Oracle Cloud Infrastructure 2024 Generative AI Professional exam ready whenever you are.
Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions:
Which statement is true about Fine-tuning and Parameter-Efficient Fine-Tuning (PEFT)?
- A. Both Fine-tuning and PEFT require the model to be trained from scratch on new data, making them equally data and computationally intensive.
- B. Fine-tuning requires training the entire model on new data, often leading to substantial computational costs, whereas PEFT involves updating only a small subset of parameters, minimizing computational requirements and data needs.
- C. PEFT requires replacing the entire model architecture with a new one designed specifically for the new task, making it significantly more data-intensive than Fine-tuning.
- D. Fine-tuning and PEFT do not involve model modification; they differ only in the type of data used for training, with Fine-tuning requiring labeled data and PEFT using unlabeled data.
Correct Answer: B 🗳️
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When is fine-tuning an appropriate method for customizing a Large Language Model (LLM)?
- A. When you want to optimize the model without any instructions
- B. When the LLM does not perform well on a task and the data for prompt engineering is too large
- C. When the LLM requires access to the latest data for generating outputs
- D. When the LLM already understands the topics necessary for text generation
Correct Answer: B 🗳️
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You create a fine-tuning dedicated AI cluster to customize a foundational model with your custom training dat a. How many unit hours arc required for fine-tuning if the cluster is active for 10 hours?
- A. 15 unit hours
- B. 30 unit hours
- C. 40 unit hours
- D. 10 unit hours
Correct Answer: D 🗳️
Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).
Which role docs a "model end point" serve in the inference workflow of the OCI Generative AI service?
- A. Evaluates the performance metrics of the custom model
- B. Updates the weights of the base model during the fine-tuning process
- C. Hosts the training data for fine-tuning custom model
- D. Serves as a designated point for user requests and model responses
Correct Answer: D 🗳️
Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).
Which is a key advantage of usingT-Few over Vanilla fine-tuning in the OCI Generative AI service?
- A. Enhanced generalization to unseen data
- B. Increased model interpretability
- C. Foster training time and lower cost
- D. Reduced model complexity
Correct Answer: C 🗳️
Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).
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