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Oracle 1z0-1122-24 Exam Syllabus Topics:

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

Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q28-Q33):

NEW QUESTION # 28
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 # 29
Which AI Ethics principle leads to the Responsible AI requirement of transparency?

  • A. Explicability
  • B. Fairness
  • C. Respect for human autonomy
  • D. Prevention of harm

Answer: A


NEW QUESTION # 30
What is the primary purpose of reinforcement learning?

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

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 # 31
In machine learning, what does the term "model training" mean?

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

Answer: B

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 # 32
What is the primary benefit of using the OCI Language service for text analysis?

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

Answer: A

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 # 33
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