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Oracle 1Z0-1122-25 Exam Syllabus Topics:

Topic	Details
Topic 1	Intro to OCI AI Services: This section tests the expertise of AI Solutions Engineers in working with OCI AI services and related APIs. It provides insights into key AI services such as language processing, computer vision, document understanding, and speech recognition, allowing professionals to leverage Oracle’s AI ecosystem for building intelligent applications.
Topic 2	Intro to DL Foundations: This section assesses the expertise of Deep Learning Engineers in understanding deep learning frameworks and architectures. It covers fundamental concepts of deep learning, introduces convolutional neural networks (CNN) for image processing, and explores sequence models like recurrent neural networks (RNN) and long short-term memory (LSTM) networks for handling sequential data.
Topic 3	Get started with OCI AI Portfolio: This section measures the proficiency of Cloud AI Specialists in exploring Oracle Cloud Infrastructure (OCI) AI services. It provides an overview of OCI AI and machine learning services, details AI infrastructure capabilities and explains responsible AI principles to ensure ethical and transparent AI development.

Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q31-Q36):

NEW QUESTION # 31
Which AI domain can be employed for identifying patterns in images and extract relevant features?

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

Answer: D

Explanation:
Computer Vision is the AI domain specifically employed for identifying patterns in images and extracting relevant features. This field focuses on enabling machines to interpret and understand visual information from the world, automating tasks that the human visual system can perform, such as recognizing objects, analyzing scenes, and detecting anomalies. Techniques in Computer Vision are widely used in applications ranging from facial recognition and image classification to medical image analysis and autonomous vehicles.

NEW QUESTION # 32
What is the difference between classification and regression in Supervised Machine Learning?

A. Classification and regression both predict continuous values.
B. Classification assigns data points to categories, whereas regression predicts continuous values.
C. Classification predicts continuous values, whereas regression assigns data points to categories.
D. Classification and regression both assign data points to categories.

Answer: B

Explanation:
In supervised machine learning, the key difference between classification and regression lies in the nature of the output they predict. Classification algorithms are used to assign data points to one of several predefined categories or classes, making it suitable for tasks like spam detection, where an email is classified as either "spam" or "not spam." On the other hand, regression algorithms predict continuous values, such as forecasting the price of a house based on features like size, location, and number of rooms. While classification answers "which category?" regression answers "how much?" or "what value?".

NEW QUESTION # 33
How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

A. They disregard model size and prioritize high-quality data only.
B. They ensure that the model size, training time, and data size are balanced for optimal results.
C. They prioritize larger model sizes to achieve better performance.
D. They focus on increasing the number of tokens while keeping the model size constant.

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 # 34
How does AI enhance human efforts?

A. By processing data at a speed and effectiveness far beyond human capability
B. By increasing the physical strength of humans
C. By deleting data humans need to handle
D. By completely replacing human workers in all tasks

Answer: A

Explanation:
AI enhances human efforts by processing large volumes of data quickly and accurately, performing complex computations that would be time-consuming or impossible for humans to handle manually. This allows humans to focus on more strategic, creative, and decision-making tasks, leveraging AI's ability to provide insights, automate repetitive processes, and support decision-making. AI does not physically enhance human capabilities, nor does it replace human workers in all tasks. Instead, it serves as an augmentation tool, amplifying human productivity and capabilities.

NEW QUESTION # 35
What is the primary benefit of using the OCI Language service for text analysis?

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

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 # 36
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Latest 1Z0-1122-25 Reliable Torrent - 1Z0-1122-25 Actual Pdf & 1Z0-1122-25 Exam Questions

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Oracle 1Z0-1122-25 Exam Syllabus Topics:

Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q31-Q36):

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