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Oracle 1z0-1122-24 Exam Syllabus Topics:

Topic	Details
Topic 1	Intro to ML Foundations: This section covers Machine Learning (ML) which is a critical area within AI, and understanding its fundamentals is crucial for anyone interested in this field. The section covers delving into the basics of ML allowing for a better grasp of how machines learn from data.
Topic 2	Intro to Generative AI & LLMs: This section is about covering generative AI which represents a powerful area of AI that involves creating new content or data. Exploring the overview of Generative AI helps in understanding its potential and applications.
Topic 3	Intro to OCI AI Services: This section is about exploring OCI AI Services and their related APIs, such as those for Language, Vision, Document Understanding, and Speech, which are essential for developers and businesses looking to integrate AI into their operations.
Topic 4	Intro to DL Foundations: This section covers Deep Learning (DL) is a subset of ML that focuses on neural networks with many layers, and understanding its core concepts is vital for working with complex models.
Topic 5	Get Started with OCI AI Portfolio: This section is about the OCI AI Portfolio which offers a comprehensive suite of services and infrastructure for developing and deploying AI models. Exploring the overview of OCI AI Services provides insight into the tools available for AI development.

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q16-Q21):

NEW QUESTION # 16
What is the primary purpose of reinforcement learning?

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

Answer: D

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 # 17
How is "Prompt Engineering" different from "Fine-tuning" in the context of Large Language Models (LLMs)?

A. Prompt Engineering modifies training data, while Fine-tuning alters the model's structure.
B. Prompt Engineering creates input prompts, while Fine-tuning retrains the model on specific data.
C. Prompt Engineering adjusts the model's parameters, while Fine-tuning crafts input prompts.
D. Both involve retraining the model, but Prompt Engineering does it more often.

Answer: B

Explanation:
In the context of Large Language Models (LLMs), Prompt Engineering and Fine-tuning are two distinct methods used to optimize the performance of AI models.
Prompt Engineering involves designing and structuring input prompts to guide the model in generating specific, relevant, and high-quality responses. This technique does not alter the model's internal parameters but instead leverages the existing capabilities of the model by crafting precise and effective prompts. The focus here is on optimizing how you ask the model to perform tasks, which can involve specifying the context, formatting the input, and iterating on the prompt to improve outputs .
Fine-tuning, on the other hand, refers to the process of retraining a pretrained model on a smaller, task-specific dataset. This adjustment allows the model to adapt its parameters to better suit the specific needs of the task at hand, effectively "specializing" the model for particular applications. Fine-tuning involves modifying the internal structure of the model to improve its accuracy and performance on the targeted tasks .
Thus, the key difference is that Prompt Engineering focuses on how to use the model effectively through input manipulation, while Fine-tuning involves altering the model itself to improve its performance on specialized tasks.

NEW QUESTION # 18
Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

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

Answer: D

Explanation:
Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.

NEW QUESTION # 19
Which capability is supported by Oracle Cloud Infrastructure Language service?

A. Converting text into images
B. Detecting objects and scenes in images
C. Analyzing text to extract structured information like sentiment or entities
D. Translating text into speech

Answer: C

Explanation:
Oracle Cloud Infrastructure (OCI) Language service is specifically designed to analyze text and extract structured information such as sentiment, entities, key phrases, and language detection. This service provides natural language processing (NLP) capabilities that help users gain insights from unstructured text data. By identifying the sentiment (positive, negative, neutral) and recognizing entities (like names, dates, or places), the service enables businesses to process large volumes of text data efficiently, aiding in decision-making processes.

NEW QUESTION # 20
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 # 21
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Try Oracle 1z0-1122-24 Dumps to achieve wonderful results

Oracle 1z0-1122-24 Exam Syllabus Topics:

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q16-Q21):

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