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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Weight	Objectives
Machine Learning Foundations	15%	- Machine Learning fundamentals 1. Reinforcement learning basics and model evaluation concepts 2. Supervised learning: regression and classification 3. Unsupervised learning: clustering and dimensionality reduction
Generative AI and Large Language Models	15%	- Generative AI concepts 1. Transformers, prompt engineering, and fine-tuning 2. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs
Introduction to OCI AI Services	20%	- OCI AI Service APIs 1. OCI Select AI and AI service use cases 2. OCI Language, Vision, Speech, and Document Understanding services
OCI AI Portfolio	15%	- Overview of OCI AI offerings 1. OCI Data Science and GPU-based compute infrastructure 2. AI Services, ML Services, and AI Infrastructure overview
OCI Generative AI and Oracle 23ai	10%	- OCI Generative AI Service features 1. Oracle 23ai Vector Database integration 2. Generative AI capabilities on OCI
Deep Learning Foundations	15%	- Deep Learning and neural networks 1. Recurrent Neural Networks, LSTMs, and sequence models 2. Convolutional Neural Networks (CNN) architectures
AI Foundations	10%	- Artificial Intelligence basics and terminology 1. AI, Machine Learning, and Deep Learning relationship 2. AI applications, use cases, and responsible AI principles

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q33-Q38):

NEW QUESTION # 33
What is the difference between classification and regression in Supervised Machine Learning?

A. Classification assigns data points to categories, whereas regression predicts continuous values.
B. Classification predicts continuous values, whereas regression assigns data points to categories.
C. Classification and regression both assign data points to categories.
D. Classification and regression both predict continuous values.

Answer: A

Explanation:
In supervised machine learning, the key difference between classification and regression lies in the nature of the output they predict. Classification algorithms are used to assign data points to one of several predefined categories or classes, making it suitable for tasks like spam detection, where an email is classified as either " spam " or " not spam. " On the other hand, regression algorithms predict continuous values, such as forecasting the price of a house based on features like size, location, and number of rooms. While classification answers " which category? " regression answers " how much? " or " what value? " .

NEW QUESTION # 34
What is the purpose of the model catalog in OCI Data Science?

A. To provide a preinstalled open source library
B. To store, track, share, and manage models
C. To create and switch between different environments
D. To deploy models as HTTP endpoints

Answer: B

Explanation:
The primary purpose of the model catalog in OCI Data Science is to store, track, share, and manage machine learning models. This functionality is essential for maintaining an organized repository where data scientists and developers can collaborate on models, monitor their performance, and manage their lifecycle. The model catalog also facilitates model versioning, ensuring that the most recent and effective models are available for deployment. This capability is crucial in a collaborative environment where multiple stakeholders need access to the latest model versions for testing, evaluation, and deployment.

NEW QUESTION # 35
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

A. It converts audio files into text.
B. It provides real-time translation of text.
C. It enhances the visual quality of documents.
D. It recognizes and extracts text from a document.

Answer: D

Explanation:
The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI ' s OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.

NEW QUESTION # 36
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 focus on increasing the number of tokens while keeping the model size constant.
C. They prioritize larger model sizes to achieve better performance.
D. They disregard model size and prioritize high-quality data only.

Answer: A

Explanation:
Large Language Models (LLMs) handle the trade-off between model size, data quality, data size, and performance by balancing these factors to achieve optimal results. Larger models typically provide better performance due to their increased capacity to learn from data; however, this comes with higher computational costs and longer training times. To manage this trade-off effectively, LLMs are designed to balance the size of the model with the quality and quantity of data used during training, and the amount of time dedicated to training. This balanced approach ensures that the models achieve high performance without unnecessary resource expenditure.

NEW QUESTION # 37
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

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

Answer: A

Explanation:
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.

NEW QUESTION # 38
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