[Q23-Q40] Updated Apr-2025 Exam Engine or PDF for the 1z0-1122-24 Tests Free Updated Today!

Rate this post

Updated Apr-2025 Exam Engine or PDF for the 1z0-1122-24 Tests Free Updated Today!

Ultimate Guide to Prepare 1z0-1122-24 with Accurate PDF Questions

Oracle 1z0-1122-24 Exam Syllabus Topics:

Topic	Details
Topic 1	Intro to AI Foundations: This section covers the fundamentals of AI are essential for understanding its wide-ranging impact and applications.
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 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 4	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 5	OCI Generative AI and Oracle 23ai: This section covers CI Generative AI Services that are a key component of Oracle’s AI offerings, and exploring these services provides a clear understanding of how Oracle supports generative AI applications.
Topic 6	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.

NEW QUESTION 23
How is “Prompt Engineering” different from “Fine-tuning” in the context of Large Language Models (LLMs)?

Prompt Engineering creates input prompts, while Fine-tuning retrains the model on specific data.

Both involve retraining the model, but Prompt Engineering does it more often.

Prompt Engineering adjusts the model’s parameters, while Fine-tuning crafts input prompts.

Prompt Engineering modifies training data, while Fine-tuning alters the model’s structure.

NEW QUESTION 24
You are working on a multilingual public announcement system. Which AI task will you use to implement it?

Speech recognition

Text summarization

Audio recording

Text to speech

NEW QUESTION 25
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

Embedding models

Translation models

Chat models

Generation models

NEW QUESTION 26
Which AI Ethics principle leads to the Responsible AI requirement of transparency?

Explicability

Prevention of harm

Respect for human autonomy

Fairness

NEW QUESTION 27
How does AI enhance human efforts?

By increasing the physical strength of humans

By deleting data humans need to handle

By completely replacing human workers in all tasks

By processing data at a speed and effectiveness far beyond human capability

NEW QUESTION 28
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

It delivers exceptional performance and scalability for complex AI tasks.

It is ideal for tasks such as text-to-speech conversion.

It offers seamless integration with social media platforms.

It provides a cost-effective solution for simple AI tasks.

NEW QUESTION 29
What is the primary purpose of reinforcement learning?

Finding relationships within data sets

Identifying patterns in data

Making predictions from labeled data

Learning from outcomes to make decisions

NEW QUESTION 30
You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?

Vision

Language

Document Understanding

Speech

NEW QUESTION 31
In machine learning, what does the term “model training” mean?

Writing code for the entire program

Performing data analysis on collected and labeled data

Analyzing the accuracy of a trained model

Establishing a relationship between input features and output

NEW QUESTION 32
Which type of machine learning is used to understand relationships within data and is not focused on making predictions or classifications?

Reinforcement learning

Unsupervised learning

Active learning

Supervised learning

NEW QUESTION 33
Which AI domain can be employed for identifying patterns in images and extract relevant features?

Anomaly Detection

Speech Processing

Natural Language Processing

Computer Vision

NEW QUESTION 34
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

They allow access to unlimited database resources.

They are free of charge for all users.

They provide high performance compute resources for fine-tuning tasks.

They provide faster internet connection speeds.

NEW QUESTION 35
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

DL is a subset of AI, and ML is a subset of DL.

AI, ML, and DL are entirely separate fields with no overlap.

ML is a subset of AI, and DL is a subset of ML.

AI is a subset of DL, which is a subset of ML.

NEW QUESTION 36
Which AI Ethics principle leads to the Responsible AI requirement of transparency?

Prevention of harm

Fairness

Respect for human autonomy

Explicability

NEW QUESTION 37
Which capability is supported by the Oracle Cloud Infrastructure Vision service?

Detecting and preventing fraud in financial transactions

Detecting vehicle number plates to issue speed citations

Generating realistic images from text

Analyzing historical data for unusual patterns

NEW QUESTION 38
What would you use Oracle AI Vector Search for?

Store business data in a cloud database.

Manage database security protocols.

Query data based on keywords.

Query data based on semantics.

NEW QUESTION 39
You are working on a project for a healthcare organization that wants to develop a system to predict the severity of patients’ illnesses upon admission to a hospital. The goal is to classify patients into three categories – Low Risk, Moderate Risk, and High Risk – based on their medical history and vital signs. Which type of supervised learning algorithm is required in this scenario?

Regression

Multi-Class Classification

Binary Classification

Clustering