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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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Oracle Cloud Infrastructure 2026 AI Foundations Associate 1z0-1122-26 Prüfungsfragen mit Lösungen (Q40-Q45):

40. Frage
A customer feedback analysis team needs to extract insights from thousands of online product reviews. They want to determine whether customers express positive or negative opinions about different aspects of a product or service. Which feature of OCI Language is helpful?

A. Named entity recognition
B. Language detection
C. Sentiment analysis
D. Key phrase extraction

Antwort: C

Begründung:
OCI Language provides pretrained natural language processing capabilities for analyzing unstructured text, including sentiment analysis. In this scenario, the requirement is specifically to determine whether customers express positive or negative opinions concerning individual aspects of a product or service. Oracle ' s OCI Language customer-feedback architecture describes extracting aspects from reviews and associating sentiments such as positive, negative, or neutral with those aspects. Oracle Docs Key phrase extraction identifies important topics or phrases, named entity recognition identifies entities such as organizations, people, or locations, and language detection determines the language in which content is written. None directly evaluates customer opinion. Sentiment analysis therefore precisely matches the business requirement because it transforms subjective review content into structured sentiment information that can be analyzed at scale.

41. Frage
Which AI Ethics principle leads to the Responsible AI requirement of transparency?

A. Prevention of harm
B. Explicability
C. Respect for human autonomy
D. Fairness

Antwort: B

42. Frage
Which capability is supported by the Oracle Cloud Infrastructure Vision service?

A. Analyzing historical data for unusual patterns
B. Generating realistic images from text
C. Detecting and preventing fraud in financial transactions
D. Detecting vehicle number plates to issue speed citations

Antwort: D

Begründung:
The Oracle Cloud Infrastructure (OCI) Vision service is designed for image analysis tasks, which includes the capability to detect and recognize objects, such as vehicle number plates. This functionality is particularly useful for applications such as automated enforcement of traffic laws, where the system can identify vehicles exceeding speed limits and issue citations based on the detected number plates. This capability leverages advanced computer vision techniques to process and analyze visual data, making it suitable for applications in public safety, transportation, and law enforcement.

43. Frage
What is the purpose of the model catalog in OCI Data Science?

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

Antwort: C

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.

44. Frage
What is the purpose of Attention Mechanism in Transformer architecture?

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

Antwort: D

Begründung:
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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45. Frage
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