1z0-1122-26 Prüfungen & 1z0-1122-26 Prüfungsübungen

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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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Oracle Cloud Infrastructure 2026 AI Foundations Associate 1z0-1122-26 Prüfungsfragen mit Lösungen (Q42-Q47):

42. Frage
What can Oracle Cloud Infrastructure Document Understanding NOT do?

A. Classify documents into different types
B. Extract text from documents
C. Generate transcript from documents
D. Extract tables from documents

Antwort: C

Begründung:
Oracle Cloud Infrastructure (OCI) Document Understanding service offers several capabilities, including extracting tables, classifying documents, and extracting text. However, it does not generate transcripts from documents. Transcription typically refers to converting spoken language into written text, which is a function associated with speech-to-text services, not document understanding services. Therefore, generating a transcript is outside the scope of what OCI Document Understanding is designed to do .

43. Frage
Which feature is NOT supported as part of the OCI Language service ' s pretrained language processing capabilities?

A. Language Detection
B. Text Classification
C. Sentiment Analysis
D. Text Generation

Antwort: D

Begründung:
The OCI Language service offers several pretrained language processing capabilities, including Text Classification, Sentiment Analysis, and Language Detection. However, it does not natively support Text Generation as a part of its core language processing capabilities. Text Generation typically involves creating new content based on input prompts, which is a feature more commonly associated with models specifically designed for natural language generation.

44. Frage
You are working on a project for a healthcare organization that wants to develop a system to predict the severity of patients ' illnesses upon admission to a hospital. The goal is to classify patients into three categories - Low Risk, Moderate Risk, and High Risk - based on their medical history and vital signs. Which type of supervised learning algorithm is required in this scenario?

A. Multi-Class Classification
B. Clustering
C. Binary Classification
D. Regression

Antwort: A

Begründung:
In this healthcare scenario, where the goal is to classify patients into three categories-Low Risk, Moderate Risk, and High Risk-based on their medical history and vital signs, a Multi-Class Classification algorithm is required. Multi-class classification is a type of supervised learning algorithm used when there are three or more classes or categories to predict. This method is well-suited for situations where each instance needs to be classified into one of several categories, which aligns with the requirement to categorize patients into different risk levels.

45. Frage
Which is NOT a capability of OCI Vision ' s image analysis?

A. Translating text in images to another language
B. Assigning classification labels to images
C. Locating and extracting text in images
D. Object detection with bounding boxes

Antwort: A

Begründung:
OCI Vision ' s image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision ' s image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision ' s core image analysis features.
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46. Frage
What is the purpose of the model catalog in OCI Data Science?

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

Antwort: A

Begründung:
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.

47. Frage
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