LATEST 1Z0-1122-25 EXAM BOOK & 1Z0-1122-25 EXAMCOLLECTION DUMPS TORRENT

Latest 1Z0-1122-25 Exam Book & 1Z0-1122-25 Examcollection Dumps Torrent

Latest 1Z0-1122-25 Exam Book & 1Z0-1122-25 Examcollection Dumps Torrent

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Oracle 1Z0-1122-25 Exam Syllabus Topics:

TopicDetails
Topic 1
  • OCI Generative AI and Oracle 23ai: This section evaluates the skills of Cloud AI Architects in utilizing Oracle’s generative AI capabilities. It includes a deep dive into OCI Generative AI services, Autonomous Database Select AI for enhanced data intelligence and Oracle Vector Search for efficient information retrieval in AI-driven applications.
Topic 2
  • Intro to DL Foundations: This section assesses the expertise of Deep Learning Engineers in understanding deep learning frameworks and architectures. It covers fundamental concepts of deep learning, introduces convolutional neural networks (CNN) for image processing, and explores sequence models like recurrent neural networks (RNN) and long short-term memory (LSTM) networks for handling sequential data.
Topic 3
  • 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.

Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q41-Q46):

NEW QUESTION # 41
What feature of OCI Data Science provides an interactive coding environment for building and training models?

  • A. Conda environment
  • B. Accelerated Data Science (ADS) SDK
  • C. Model catalog
  • D. Notebook sessions

Answer: D

Explanation:
In OCI Data Science, Notebook sessions provide an interactive coding environment that is essential for building, training, and deploying machine learning models. These sessions allow data scientists to write and execute code in real time, offering a flexible environment for data exploration, model experimentation, and iterative development. The integration with various OCI services and support for popular machine learning frameworks further enhances the utility of Notebook sessions, making them a crucial tool in the data science workflow.


NEW QUESTION # 42
In machine learning, what does the term "model training" mean?

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

Answer: A

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 # 43
You are working on a multilingual public announcement system. Which AI task will you use to implement it?

  • A. Text to speech
  • B. Speech recognition
  • C. Audio recording
  • D. Text summarization

Answer: A

Explanation:
For a multilingual public announcement system, the AI task that would be most relevant is "Text to Speech" (TTS). This task involves converting written text into spoken words, which can then be broadcasted over public address systems in multiple languages.
Text to Speech technology is crucial for creating accessible and understandable announcements in different languages, especially in environments like airports, train stations, or public events where clear verbal communication is essential. The TTS system would be configured to support multiple languages, allowing it to deliver announcements to diverse audiences effectively .


NEW QUESTION # 44
Which capability is supported by Oracle Cloud Infrastructure Language service?

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

Answer: D

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 # 45
What is the primary purpose of reinforcement learning?

  • A. Identifying patterns in data
  • B. Making predictions from labeled data
  • C. Finding relationships within data sets
  • 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 # 46
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