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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Objectives
OCI Generative AI and Oracle Database AI Capabilities	- AI Application Frameworks 1. Language frameworks 2. Retrieval and AI application concepts - Oracle AI Database 1. AI capabilities in Oracle Database 2. Vector database concepts - OCI Generative AI 1. OCI Generative AI services 2. Generative AI models and applications
Artificial Intelligence and Machine Learning Fundamentals	- Artificial Intelligence Concepts 1. AI use cases and applications 2. AI fundamentals and terminology - Deep Learning Fundamentals 1. Convolutional and sequence models 2. Neural networks - Machine Learning Fundamentals 1. Supervised and unsupervised learning 2. Machine learning models and architectures
Generative AI and Large Language Models	- Large Language Models 1. Language models and generative AI applications 2. LLM fundamentals - Generative AI Fundamentals 1. Generative AI concepts and capabilities 2. Generative AI use cases
Oracle AI and Machine Learning Services	- OCI Machine Learning Services 1. Machine learning capabilities in OCI 2. OCI Data Science and machine learning workflows - Oracle AI Stack 1. AI infrastructure 2. AI data and machine learning services - OCI AI Services 1. Vision 2. Speech 3. Document Understanding 4. Language

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q46-Q51):

NEW QUESTION # 46
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 provide faster internet connection speeds.
C. They provide high performance compute resources for fine-tuning tasks.
D. They are free of charge for all users.

Answer: C

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 # 47
Which type of machine learning is used to understand relationships within data and is not focused on making predictions or classifications?

A. Active learning
B. Reinforcement learning
C. Supervised learning
D. Unsupervised learning

Answer: D

Explanation:
Unsupervised learning is a type of machine learning that focuses on understanding relationships within data without the need for labeled outcomes. Unlike supervised learning, which requires labeled data to train models to make predictions or classifications, unsupervised learning works with unlabeled data and aims to discover hidden patterns, groupings, or structures within the data.
Common applications of unsupervised learning include clustering, where the algorithm groups data points into clusters based on similarities, and association, where it identifies relationships between variables in the dataset. Since unsupervised learning does not predict outcomes but rather uncovers inherent structures, it is ideal for exploratory data analysis and discovering previously unknown patterns in data .

NEW QUESTION # 48
Which capability is supported by Oracle Cloud Infrastructure Language service?

A. Translating text into speech
B. Converting text into images
C. Detecting objects and scenes in images
D. Analyzing text to extract structured information like sentiment or entities

Answer: D

Explanation:
Oracle Cloud Infrastructure (OCI) Language service is specifically designed to analyze text and extract structured information such as sentiment, entities, key phrases, and language detection. This service provides natural language processing (NLP) capabilities that help users gain insights from unstructured text data. By identifying the sentiment (positive, negative, neutral) and recognizing entities (like names, dates, or places), the service enables businesses to process large volumes of text data efficiently, aiding in decision-making processes.

NEW QUESTION # 49
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

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

Answer: C

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 # 50
Which feature is NOT available as part of OCI Speech capabilities?

A. Uses extensive data science experience to operate
B. Transcribes audio and video files into text
C. Provides timestamped, grammatically accurate transcriptions
D. Supports multiple languages including English, Spanish, and Portuguese

Answer: A

Explanation:
OCI Speech capabilities are designed to be user-friendly and do not require extensive data science experience to operate. The service provides features such as transcribing audio and video files into text, offering grammatically accurate transcriptions, supporting multiple languages, and providing timestamped outputs.
These capabilities are built to be accessible to a broad range of users, making speech-to-text conversion seamless and straightforward without the need for deep technical expertise.

NEW QUESTION # 51
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