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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q24-Q29):

NEW QUESTION # 24
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

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

Answer: A

NEW QUESTION # 25
How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

A. They prioritize larger model sizes to achieve better performance.
B. They ensure that the model size, training time, and data size are balanced for optimal results.
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: B

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 # 26
Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

A. Anomaly Detection
B. Natural Language Processing
C. Natural Language Processing
D. Computer Vision

Answer: C

Explanation:
Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.

NEW QUESTION # 27
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

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

Answer: A

Explanation:
Oracle Cloud Infrastructure Supercluster is designed to deliver exceptional performance and scalability for complex AI tasks. The primary benefit of this infrastructure is its ability to handle demanding AI workloads, offering high-performance computing (HPC) capabilities that are crucial for training large-scale AI models and processing massive datasets. The architecture of the Supercluster ensures low-latency networking, efficient resource allocation, and high-throughput processing, making it ideal for AI tasks that require significant computational power, such as deep learning, data analytics, and large-scale simulations.

NEW QUESTION # 28
What is the primary benefit of using the OCI Language service for text analysis?

A. It only works with structured data.
B. It requires extensive machine learning expertise to use.
C. It allows for text analysis at scale without machine learning expertise.
D. It provides image processing capabilities.

Answer: C

Explanation:
The primary benefit of using the OCI Language service for text analysis is its ability to scale text analysis without requiring users to have extensive machine learning expertise. The service abstracts the complexities of machine learning, allowing businesses to easily process and analyze large amounts of text data through pre- built models. This accessibility makes it possible for a broader range of users to leverage advanced text analysis capabilities, facilitating insights from textual data without needing to develop and train models from scratch.

NEW QUESTION # 29
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