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Oracle 1z0-1122-24 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	Intro to AI Foundations: This section covers the fundamentals of AI are essential for understanding its wide-ranging impact and applications.
Topic 3	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.
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	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 6	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.

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q23-Q28):

NEW QUESTION # 23
What is the difference between classification and regression in Supervised Machine Learning?

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

Answer: A

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 # 24
Which AI domain can be employed for identifying patterns in images and extract relevant features?

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

Answer: C

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 # 25
How does AI enhance human efforts?

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

Answer: D

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 # 26
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

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

Answer: A

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 # 27
In machine learning, what does the term "model training" mean?

A. Performing data analysis on collected and labeled data
B. Analyzing the accuracy of a trained model
C. Writing code for the entire program
D. Establishing a relationship between input features and output

Answer: D

Explanation:
In machine learning, "model training" refers to the process of teaching a model to make predictions or decisions by learning the relationships between input features and the corresponding output. During training, the model is fed a large dataset where the inputs are paired with known outputs (labels). The model adjusts its internal parameters to minimize the error between its predictions and the actual outputs. Over time, the model learns to generalize from the training data to make accurate predictions on new, unseen data.

NEW QUESTION # 28
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Real Oracle 1z0-1122-24 Dumps Attempt the Exam in the Optimal Way

Oracle 1z0-1122-24 Exam Syllabus Topics:

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q23-Q28):

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