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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 Generative AI & LLMs: This section tests the abilities of AI Developers to understand generative AI and large language models. It introduces the principles of generative AI, explains the fundamentals of large language models (LLMs), and discusses the core workings of transformers, prompt engineering, instruction tuning, and LLM fine-tuning for optimizing AI-generated content.
Topic 3	Intro to ML Foundations: This section evaluates the knowledge of Machine Learning Engineers in understanding machine learning principles and methodologies. It explores the basics of supervised learning, focusing on regression and classification techniques, along with unsupervised learning methods such as clustering and anomaly detection. It also introduces reinforcement learning fundamentals, helping professionals grasp the different approaches used to train AI models.
Topic 4	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.
Topic 5	Intro to AI Foundations: This section of the exam measures the skills of AI Practitioners and Data Analysts in understanding the fundamentals of artificial intelligence. It covers key concepts, AI applications across industries, and the types of data used in AI models. It also explains the differences between artificial intelligence, machine learning, and deep learning, providing clarity on how these technologies interact and complement each other.

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Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q29-Q34):

NEW QUESTION # 29
What distinguishes Generative AI from other types of AI?

A. Generative AI creates diverse content such as text, audio, and images by learning patterns from existing data.
B. Generative AI involves training models to perform tasks without human intervention.
C. Generative AI focuses on making decisions based on user interactions.
D. Generative AI uses algorithms to predict outcomes based on past data.

Answer: A

Explanation:
Generative AI is distinct from other types of AI in that it focuses on creating new content by learning patterns from existing data. This includes generating text, images, audio, and other types of media. Unlike AI that primarily analyzes data to make decisions or predictions, Generative AI actively creates new and original outputs. This ability to generate diverse content is a hallmark of Generative AI models like GPT-4, which can produce human-like text, create images, and even compose music based on the patterns they have learned from their training data.

NEW QUESTION # 30
What would you use Oracle AI Vector Search for?

A. Query data based on semantics.
B. Store business data in a cloud database.
C. Query data based on keywords.
D. Manage database security protocols.

Answer: A

Explanation:
Oracle AI Vector Search is designed to query data based on semantics rather than just keywords. This allows for more nuanced and contextually relevant searches by understanding the meaning behind the words used in a query. Vector search represents data in a high-dimensional vector space, where semantically similar items are placed closer together. This capability makes it particularly powerful for applications such as recommendation systems, natural language processing, and information retrieval where the meaning and context of the data are crucial .

NEW QUESTION # 31
What is the primary purpose of reinforcement learning?

A. Learning from outcomes to make decisions
B. Finding relationships within data sets
C. Making predictions from labeled data
D. Identifying patterns in data

Answer: A

Explanation:
Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve a certain goal. The agent receives feedback in the form of rewards or penalties based on the outcomes of its actions, which it uses to learn and improve its decision-making over time. The primary purpose of reinforcement learning is to enable the agent to learn optimal strategies by interacting with its environment, thereby maximizing cumulative rewards. This approach is commonly used in areas such as robotics, game playing, and autonomous systems.

NEW QUESTION # 32
How does AI enhance human efforts?

A. By processing data at a speed and effectiveness far beyond human capability
B. By deleting data humans need to handle
C. By increasing the physical strength of humans
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 # 33
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

A. AI is a subset of DL, which is a subset of ML.
B. DL is a subset of AI, and ML is a subset of DL.
C. AI, ML, and DL are entirely separate fields with no overlap.
D. ML is a subset of AI, and DL is a subset of ML.

Answer: D

Explanation:
Artificial Intelligence (AI) is the broadest field encompassing all technologies that enable machines to perform tasks that typically require human intelligence. Within AI, Machine Learning (ML) is a subset focused on the development of algorithms that allow systems to learn from and make predictions or decisions based on data. Deep Learning (DL) is a further subset of ML, characterized by the use of artificial neural networks with many layers (hence "deep").
In this hierarchy:
AI includes all methods to make machines intelligent.
ML refers to the methods within AI that focus on learning from data.
DL is a specialized field within ML that deals with deep neural networks.

NEW QUESTION # 34
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Valid 1Z0-1122-25 Exam Online, 1Z0-1122-25 Valid Study Guide

Oracle 1Z0-1122-25 Exam Syllabus Topics:

Oracle 1Z0-1122-25 Valid Study Guide, 1Z0-1122-25 Knowledge Points

Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q29-Q34):

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