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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q27-Q32):

NEW QUESTION # 27
How does Oracle Cloud Infrastructure Document Understanding service facilitate business processes?

A. By analyzing sentiment in text documents
B. By generating lifelike speech from documents
C. By transcribing spoken language
D. By automating data extraction from documents

Answer: D

Explanation:
Oracle Cloud Infrastructure (OCI) Document Understanding service facilitates business processes by automating data extraction from documents. This service leverages machine learning to identify, classify, and extract relevant information from various document types, reducing the need for manual data entry and improving efficiency in document processing workflows. Automation of these tasks enables organizations to streamline operations and reduce errors associated with manual data handling.

NEW QUESTION # 28
Which AI Ethics principle leads to the Responsible AI requirement of transparency?

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

Answer: B

Explanation:
Explicability is the AI Ethics principle that leads to the Responsible AI requirement of transparency. This principle emphasizes the importance of making AI systems understandable and interpretable to humans.
Transparency is a key aspect of explicability, as it ensures that the decision-making processes of AI systems are clear and comprehensible, allowing users to understand how and why a particular decision or output was generated. This is critical for building trust in AI systems and ensuring that they are used responsibly and ethically.
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NEW QUESTION # 29
What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?

A. Directly predicting the final output
B. Storing the input pixel values
C. Capturing the internal representation of the raw image data
D. Providing labels for the output neurons

Answer: C

Explanation:
In an Artificial Neural Network (ANN) designed for recognizing handwritten digits, the hidden layers serve the crucial function of capturing the internal representation of the raw image data. These layers learn to extract and represent features such as edges, shapes, and textures from the input pixels, which are essential for distinguishing between different digits. By transforming the input data through multiple hidden layers, the network gradually abstracts the raw pixel data into higher-level representations, which are more informative and easier to classify into the correct digit categories.

NEW QUESTION # 30
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

A. Translation models
B. Generation models
C. Chat models
D. Embedding models

Answer: A

Explanation:
The OCI Generative AI service offers various categories of pretrained foundational models, including Embedding models, Chat models, and Generation models. These models are designed to perform a wide range of tasks, such as generating text, answering questions, and providing contextual embeddings. However, Translation models, which are typically used for converting text from one language to another, are not a category available in the OCI Generative AI service ' s current offerings. The focus of the OCI Generative AI service is more aligned with tasks related to text generation, chat interactions, and embedding generation rather than direct language translation.

NEW QUESTION # 31
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

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

Answer: D

NEW QUESTION # 32
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