Oracle AI Foundation Practice Exam

Few-shot prompting

Which technique providing explicit examples in a prompt to guide an LLM's response?

OCI Data Science

John has successfully trained a machine learning model using OCI. He now needs to deploy it for real-time predictions where it can process user inputs and generate responses. Which OCI service should he use for deployment?

OCI Vault

Which of these components is NOT a part of OCI AI Infrastructure?

SRT file support

Emma works for a media company that produces video content for online platforms. She needs to add closed captions to their videos for accessibility. Which OCI Speech feature should Emma use?

Text classification

John works in a news aggregation platform and wants to automatically categorize articles into topics like "Politics", "Technology", and "Sports". Which feature of OCI Language would help him?

Key-value extraction

Mark is analyzing customer receipts and wants to automatically find and save details such as merchant name, transaction date, and total amount for record-keeping. Which OCI Vision feature should he use?

Recurrent Neural Network (RNN)

You are working on a deep learning project to generate music. Which type of neural network is best suited for this task?

Confidence scoring

John needs to analyze the accuracy of OCI Speech transcriptions for a legal case. He wants to evaluate how sure the model is about each word in the transcription. Which feature should he use?

H100

You need a suitable GPU for massive-scale (HPC) AI training and inference workloads. Which NVIDIA GPU are you most likely to choose?

Convolutional Neural Network (CNN)

You are training a deep learning model to recognize faces. What type of neural network is best suited for this task?

Deep Learning

You're developing an image classification software that can identify specific objects. Which AI subset would you use?

Machine Learning

A company wants to automate its email filtering system to reduce spam. Which AI technique would you recommend?

It selectively updates only a fraction of the model's weights.

Which statement correctly explains the reason T-Fine tuning reduces cost and training time as compared to traditional fine-tuning.

To adjust the pretrained model's parameters using a smaller, task-specific dataset, improving its performance on specific tasks

What is the primary goal of fine-tuning a Large Language Model (LLM)?

Artificial Intelligence

A self-driving car needs to detect pedestrians and make safe lane changes. Which AI concept is being applied here?

By enabling natural language prompts instead of SQL code

How does Select AI enhance the interaction with Oracle Autonomous Database?

This layer is optional, and it processes and transforms inputs from the network's weights and activation functions.

What is the purpose of the hidden layer in an artificial neural network?

Spam detection

Which of these is NOT a common application of unsupervised machine learning?

LLMs are pretrained on a large text corpus whereas ML models need to be trained on custom data.

Which statement best describes the primary difference between Large Language Models (LLMs) and traditional Machine Learning (ML) models?

Complex data with non-human interpretable features

What type of data is most likely to be used with deep learning algorithms?

Recurrent Neural Network (RNN)

You are writing poems. You need your computer to help you complete your lines by suggesting right words. Which deep learning model is best suited for this task?

They are individual units into which a piece of text is divided during processing by the model.

What role do tokens play in Large Language Models (LLMs)?

It converts elements like numbers, dates, and URLs into standard readable formats.

How does normalization improve the readability of transcriptions in OCI Speech?

K-Nearest Neighbors (KNN)

Which algorithm is a non-parametric approach for supervised learning?

AI should be lawful, ethical, and robust.

Which of these summarizes the three guiding principles for AI to be trustworthy?

It learns patterns in unstructured data without requiring labeled training data.

Which statement best describes the pretraining process of a Generative AI model?

It quantifies the cost of incorrect predictions.

What is the role of the loss function in supervised learning algorithms?

RNNs struggle with long-range dependencies due to the vanishing gradient problem.

What is the primary limitation of Recurrent Neural Networks (RNNs) when processing long sequences?

By loading ONNX models directly into the database

How does Database 23ai allow ONNX models to be used for AI vector search?

Object detection

Lisa runs an automated security system that monitors parking lots using cameras. She wants to locate and label vehicles and license plates in each frame. Which OCI Vision feature should she use?

Predicting outcomes from new data points

What is the primary function of the inference process in machine learning?

It connects to an LLM, infers the query intent, and formulates the SQL command.

How does Select AI generate SQL queries from natural language questions?

A100

You need a suitable GPU for small or medium scale AI training and inference workloads. Which NVIDIA GPU are you most likely to choose?

Supervised Learning

A streaming service wants to recommend TV shows based on user behavior. Which machine learning approach should be used?

Document classification

Which OCI Vision feature is useful for identifying whether a document is an invoice, receipt, or resume, based on its appearance and keywords?

Tagging

David is transcribing a customer support call using OCI Speech. The call contains some profane language, and he wants to retain the original words but mark them as inappropriate rather than discarding them. Which profanity filtering option should David use?

It contains the desired output or class labels.

What is the role of a target variable in supervised learning?

Regression

What technique is used to predict the price of a house based on its features?

It serves as a repository for storing, tracking, and managing machine learning models.

What is the purpose of the Model Catalog in OCI Data Science?

Time series data

You are training a deep learning model to predict stock prices. What type of data is this an example of?