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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: OCI Generative AI and Oracle 23ai	10%	- Discuss Autonomous Database Select AI - Describe OCI Generative AI Services - Discuss Oracle Vector Search
Topic 2: Intro to Generative AI and LLMs	15%	- Discuss Generative AI Overview - Discuss Large Language Models Fundamentals - Explain LLM Fine Tuning - Explain Prompt Engineering and Instruction Tuning - Explain Transformers Fundamentals
Topic 3: Intro to DL Foundations	15%	- Explain Sequence Models (RNN and LSTM) - Explain Convolutional Models (CNN) - Discuss Deep Learning Fundamentals
Topic 4: Intro to AI Foundations	10%	- Explain AI vs ML vs DL - Discuss AI Basics - Discuss AI Applications and Types of Data
Topic 5: Intro to ML Foundations	15%	- Discuss Supervised Learning Fundamentals 1. Classification 2. Regression - Discuss Reinforcement Learning Fundamentals - Discuss Unsupervised Learning Fundamentals - Explain Machine Learning Basics
Topic 6: Get started with OCI AI Portfolio	15%	- Discuss OCI AI Services Overview - Discuss OCI AI Infrastructure Overview - Explain Responsible AI - Discuss OCI ML Services Overview
Topic 7: Intro to OCI AI Services	20%	- OCI Vision - OCI Document Understanding - OCI Speech - OCI Language

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Oracle Cloud Infrastructure 2026 AI Foundations Associate 認定 1z0-1122-26 試験問題 (Q48-Q53):

質問 # 48
What does " fine-tuning " refer to in the context of OCI Generative AI service?

A. Upgrading the hardware of the AI clusters
B. Adjusting the model parameters to improve accuracy
C. Doubling the neural network layers
D. Encrypting the data for security reasons

正解：B

解説：
Fine-tuning in the context of the OCI Generative AI service refers to the process of adjusting the parameters of a pretrained model to better fit a specific task or dataset. This process involves further training the model on a smaller, task-specific dataset, allowing the model to refine its understanding and improve its performance on that specific task. Fine-tuning is essential for customizing the general capabilities of a pretrained model to meet the particular needs of a given application, resulting in more accurate and relevant outputs. It is distinct from other processes like encrypting data, upgrading hardware, or simply increasing the complexity of the model architecture.

質問 # 49
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

A. They allow access to unlimited database resources.
B. They are free of charge for all users.
C. They provide high performance compute resources for fine-tuning tasks.
D. They provide faster internet connection speeds.

正解：C

解説：
The primary advantage of using dedicated AI clusters in the Oracle Cloud Infrastructure (OCI) Generative AI service is the provision of high-performance compute resources that are specifically optimized for fine-tuning tasks. Fine-tuning is a critical step in the process of adapting pre-trained models to specific tasks, and it requires significant computational power. Dedicated AI clusters in OCI are designed to deliver the necessary performance and scalability to handle the intense workloads associated with fine-tuning large language models (LLMs) and other AI models, ensuring faster processing and more efficient training.

質問 # 50
What is the purpose of Attention Mechanism in Transformer architecture?

A. Weigh the importance of different words within a sequence and understand the context.
B. Apply a specific function to each word individually.
C. Break down a sentence into smaller pieces called tokens.
D. Convert tokens into numerical forms (vectors) that the model can understand.

正解：A

解説：
The purpose of the Attention Mechanism in Transformer architecture is to weigh the importance of different words within a sequence and understand the context. In essence, the attention mechanism allows the model to focus on specific parts of the input sequence when producing an output, which is crucial for understanding context and maintaining coherence over long sequences. It does this by assigning different weights to different words in the sequence, enabling the model to capture relationships between words that are far apart and to emphasize relevant parts of the input when generating predictions.
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質問 # 51
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

A. It provides a cost-effective solution for simple AI tasks.
B. It delivers exceptional performance and scalability for complex AI tasks.
C. It is ideal for tasks such as text-to-speech conversion.
D. It offers seamless integration with social media platforms.

正解：B

質問 # 52
What is the benefit of using embedding models in OCI Generative AI service?

A. They facilitate semantic searches.
B. They enable creating detailed graphics.
C. They optimize the use of computational resources.
D. They simplify managing databases.

正解：A

解説：
Embedding models in the OCI Generative AI service are designed to represent text, phrases, or other data types in a dense vector space, where semantically similar items are located closer to each other. This representation enables more effective semantic searches, where the goal is to retrieve information based on the meaning and context of the query, rather than just exact keyword matches.
The benefit of using embedding models is that they allow for more nuanced and contextually relevant searches. For example, if a user searches for " financial reports, " an embedding model can understand that " quarterly earnings " is semantically related, even if the exact phrase does not appear in the document. This capability greatly enhances the accuracy and relevance of search results, making it a powerful tool for handling large and diverse datasets .

質問 # 53
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