Give Push to your Success with Oracle Cloud Infrastructure 1Z0-1122-25 Exam Questions [Q16-Q34]

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Give Push to your Success with Oracle Cloud Infrastructure 1Z0-1122-25 Exam Questions

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NO.16 What feature of OCI Data Science provides an interactive coding environment for building and training models?

Accelerated Data Science (ADS) SDK

Conda environment

Model catalog

Notebook sessions

NO.17 Which is NOT a capability of OCI Vision’s image analysis?

Locating and extracting text in images

Translating text in images to another language

Assigning classification labels to images

Object detection with bounding boxes

NO.18 Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

Natural Language Processing

Computer Vision

Natural Language Processing

Anomaly Detection

NO.19 What is the benefit of using embedding models in OCI Generative AI service?

They optimize the use of computational resources.

They simplify managing databases.

They facilitate semantic searches.

They enable creating detailed graphics.

NO.20 Which AI domain can be employed for identifying patterns in images and extract relevant features?

Anomaly Detection

Speech Processing

Natural Language Processing

Computer Vision

NO.21 What is the key feature of Recurrent Neural Networks (RNNs)?

They process data in parallel.

They are primarily used for image recognition tasks.

They have a feedback loop that allows information to persist across different time steps.

They do not have an internal state.

NO.22 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.

NO.23 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

NO.24 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

NO.25 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.

NO.26 How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

They prioritize larger model sizes to achieve better performance.

They focus on increasing the number of tokens while keeping the model size constant.

They disregard model size and prioritize high-quality data only.

They ensure that the model size, training time, and data size are balanced for optimal results.

NO.27 Which feature is NOT supported as part of the OCI Language service’s pretrained language processing capabilities?

Text Classification

Sentiment Analysis

Language Detection

Text Generation

NO.28 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

NO.29 Which algorithm is primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN)?

Gradient Descent

Backpropagation

Random Forest

Support Vector Machine

NO.30 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.

NO.31 Which feature of OCI Speech helps make transcriptions easier to read and understand?

Audio tuning

Timestamping

Profanity filtering

Text normalization

NO.32 What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?

Capturing the internal representation of the raw image data

Providing labels for the output neurons

Directly predicting the final output

Storing the input pixel values

Oracle 1Z0-1122-25 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	Intro to Generative AI & LLMs: This section tests the abilities of AI Developers to understand generative AI and large language models. It introduces the principles of generative AI, explains the fundamentals of large language models (LLMs), and discusses the core workings of transformers, prompt engineering, instruction tuning, and LLM fine-tuning for optimizing AI-generated content.
Topic 4	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.