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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q27-Q32):

NEW QUESTION # 27
How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

A. They ensure that the model size, training time, and data size are balanced for optimal results.
B. They prioritize larger model sizes to achieve better performance.
C. They focus on increasing the number of tokens while keeping the model size constant.
D. They disregard model size and prioritize high-quality data only.

Answer: A

NEW QUESTION # 28
What is the purpose of Attention Mechanism in Transformer architecture?

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

Answer: D

Explanation:
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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NEW QUESTION # 29
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

A. Generation models
B. Embedding models
C. Chat models
D. Translation models

Answer: D

Explanation:
The OCI Generative AI service offers various categories of pretrained foundational models, including Embedding models, Chat models, and Generation models. These models are designed to perform a wide range of tasks, such as generating text, answering questions, and providing contextual embeddings. However, Translation models, which are typically used for converting text from one language to another, are not a category available in the OCI Generative AI service ' s current offerings. The focus of the OCI Generative AI service is more aligned with tasks related to text generation, chat interactions, and embedding generation rather than direct language translation.

NEW QUESTION # 30
How does AI enhance human efforts?

A. By completely replacing human workers in all tasks
B. By processing data at a speed and effectiveness far beyond human capability
C. By deleting data humans need to handle
D. By increasing the physical strength of humans

Answer: B

Explanation:
AI enhances human efforts by processing large volumes of data quickly and accurately, performing complex computations that would be time-consuming or impossible for humans to handle manually. This allows humans to focus on more strategic, creative, and decision-making tasks, leveraging AI ' s ability to provide insights, automate repetitive processes, and support decision-making. AI does not physically enhance human capabilities, nor does it replace human workers in all tasks. Instead, it serves as an augmentation tool, amplifying human productivity and capabilities.

NEW QUESTION # 31
You are training a deep learning model to classify images. What is the primary function of the convolutional layer?

A. To classify the input image.
B. To reduce the spatial dimensions of the input image.
C. To generate new images.
D. To detect specific features in the input image.

Answer: D

Explanation:
A convolutional layer is designed to learn local visual features from an input image. During training, small learnable filters move across the image and respond to patterns such as edges, corners, textures, and progressively more complex structures. The resulting feature maps preserve useful spatial relationships while transforming raw pixels into representations that later layers can use. Oracle documentation recognizes convolutional neural networks as suitable neural-network architectures for visual data and identifies architectures such as ResNet for processing images. Oracle Docs The convolutional layer itself does not primarily generate images or make the final classification decision. Reducing spatial dimensions is normally performed through pooling or strided operations. Therefore, detecting specific features in the input image is the correct function.

NEW QUESTION # 32
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