AI Foundations 2025

You are working on a multilingual public announcement system. Which Al task will you use to implement it?. Text to speech. Text summarization. Speech recognition. Audio recording.

Which Al domain is associated with tasks such as identifying the sentiment of text and translating text between languages?. Anomaly Detection. Natural Language Processing. Computer Vision. Speech Processing.

Emma works for a customer feedback analysis team and needs to extract insights from thousands of online product reviews. She wants to determine if customers express positive or negative opinions about different aspects, such as price, quality, and customer service. Which feature of OCI Language is helpful for her?. Key phrase extraction. Named entity recognition. Language detection. Sentiment analysis.

Which capability is supported by the Oracle Cloud Infrastructure Vision service?. Detecting and preventing fraud in financial transactions. Generating realistic images from text. Detecting vehicle number plates to issue speed citations. Analyzing historical data for unusual patterns.

Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?. It provides real-time translation of text. It converts audio files into text. It recognizes and extracts text from a document. It enhances the visual quality of documents.

What can Oracle Cloud Infrastructure Document Understanding NOT do?. Generate transcript from documents. Classify documents into different types. Extract tables from documents. Extract text from documents.

Lisa is working on a project that involves transcribing thousands of audio files stored in Oracle Cloud. She wants to process multiple filles efficiently instead of transcribing them one by one. Which OCI Speech feature should Lisa use?. Confidence scoring. Profanity filtering. Batch support. Time stamping.

How does Oracle Cloud Infrastructure Document Understanding service facilitate business processes?. By automating data extraction from documents. By generating lifelike speech from documents. By transcribing spoken language. By analyzing sentiment in text documents.

You are part of the medical transcription team and need to automate transcription tasks. Which OCI Al service are you most likely to use?. Document Understanding. Vision. Speech. Language.

Which feature of OCI Speech helps make transcriptions easier to read and understand?. Timestamping. Audio tuning. Text normalization. Profanity filtering.

What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for Al workloads?. It offers seamless integration with social media platforms. It is ideal for tasks such as text-to-speech conversion. It delivers exceptional performance and scalability for complex Al tasks. It provides a cost-effective solution for simple Al tasks.

Emma is developing a customer support chatbot for an e-commerce website. The chatbot needs to provide accurate and up-to-date return policies, which change frequently. She initially tries fine-tuning but realizes that the return policy data changes too often. Which approach should Emma use instead?. Zero-shot prompting. Prompt Engineering. Reinforcement Learning. Retrieval-Augmented Generation.

What key objective does machine learning strive to achieve?. Enabling computers to learn and improve from experience. Explicitly programming computers. Improving computer hardware. Creating algorithms to solve complex problems.

In machine learning, what does the term "model training" mean?. Analyzing the accuracy of a trained model. Writing code for the entire program. Performing data analysis on collected and labeled data. Establishing a relationship between input features and output.

What is a key advantage of using dedicated Al clusters in the OCI Generative Al service?. They provide faster internet connection speeds. They provide high performance compute resources for fine-tuning tasks. They are free of charge for all users. They allow access to unlimited database resources.

Which is NOT a category of pretrained foundational models available in the OCI Generative Al service?. Chat models. Translation models. Generation models. Embedding models.

What is the benefit of using embedding models in OCI Generative Al service?. They simplify managing databases. They facilitate semantic searches. They optimize the use of computational resources. They enable creating detailed graphics.

What does "fine-tuning" refer to in the context of OCI Generative Al service?. Doubling the neural network layers. Upgrading the hardware of the Al clusters. Encrypting the data for security reasons. Adjusting the model parameters to improve accuracy.

You are training a deep learning model to classify images. What is the primary function of the convolutional layer?. To detect specific features in the input image. To generate new images. To classify the input image. To reduce the spatial dimensions of the input image.

What is the primary purpose of reinforcement learning?. Making predictions from labeled data. Learning from outcomes to make decisions. Finding relationships within data sets. Identifying pattems in data.

How does Al enhance human efforts?. By processing data at a speed and effectiveness far beyond human capability. By completely replacing human workers in all tasks. By increasing the physical strength of humans. By deleting data humans need to handle.

What is the key feature of Recurrent Neural Networks (RNNs)?. They do not have an internal state. They process data in parallel. They have a feedback loop that allows information to persist across different time steps. They are primarily used for image recognition tasks.

Which Al Ethics principle leads to the Responsible Al requirement of transparency?. Respect for human autonomy. Prevention of harm. Fairness. Explicability.

Which type of machine learning is used to understand relationships within data and is not focused on making predictions or classifications?. Supervised learning. Unsupervised learning. Reinforcement learning. Active learning.

What would you use Oracle Al Vector Search for?. Store business data in a cloud database. Query data based on semantics. Query data based on keywords. Manage database security protocols.

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 ensure that the model size, training time, and data size are balanced for optimal results. They disregard model size and prioritize high-quality data only.

You're analyzing customer feedback forms to identify common complaints. Which machine learning approach would you use?. Supervised Learning. Deep Learning. Reinforcement Learning. Unsupervised Learning.

What is "in-context learning" in the realm of Large Language Models (LLMs)?. Teaching a model through zero-shot learning. Providing a few examples of a target task via the input prompt. Training a model on a diverse range of tasks. Modifying the behavior of a pretrained LLM permanently.

What distinguishes Generative Al from other types of Al?. Generative Al involves training models to perform tasks without human intervention. Generative Al focuses on making decisions based on user interactions. Generative Al creates diverse content such as text, audio, and images by learning patterns from existing data. Generative Al uses algorithms to predict outcomes based on past data.

Which is NOT a capability of OCI Vision's image analysis?. Locating and extracting text in images. Translating text in images to another language. Object detection with bounding boxes. Assigning classification labels to images.

Which feature is NOT supported as part of the OCI Language service's pretrained language processing capabilities?. Sentiment Analysis. Language Detection. Text Classification. Text Generation.

What is the primary benefit of using the OCI Language service for text analysis?. It requires extensive machine learning expertise to use. It provides image processing capabilities. It allows for text analysis at scale without machine learning expertise. It only works with structured data.

What feature of OCI Data Science provides an interactive coding environment for building and training models?. Conda environment. Model catalog. Accelerated Data Science (ADS) SDK. Notebook sessions.

Which component in OCI Data Science provides an interactive coding environment for building and training models?. Data Science Jobs. Notebook Sessions. Conda Environments. Model Catalog.

You are training a deep learning model to predict user behavior. What type of data is this an example of?. Time-series data. Image data. Text data. Sequential data.

Which algorithm is primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN)?. Support Vector Machine. Random Forest. Gradient Descent. Backpropagation.

What is the role of the self-attention mechanism in a transformer model?. It assigns different importance to each word in a sequence based on context. It forces the model to only focus on the most recent words in a sequence. It replaces all previous deep learning techniques for text processing. It memorizes and retrieves specific words from past training examples.

What role do Transformers perform in Large Language Models (LLMs)?. Provide a mechanism to process sequential data in parallel and capture long-range dependencies. Image recognition tasks in LLMs. Limit the ability of LLMs to handle large datasets by imposing strict memory constraints. Manually engineer features in the data before training the model.

You are training a logistic regression model to classify emails as spam or not spam. The model is currently classifying too many emails as spam. What would you do to adjust the model?. Increase the regularization parameter. Increase the threshold value for classification. Decrease the weight of the feature representing the presence of certain keywords. Decrease the number of iterations.

What is the difference between classification and regression in Supervised Machine Learning?. Classification assigns data points to categories, whereas regression predicts continuous values. Classification predicts continuous values, whereas regression assigns data points to categories. Classification and regression both predict continuous values. Classification and regression both assign data points to categories.

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?. Multi-Class Classification. Clustering. Binary Classification. Regression.

What are Convolutional Neural Networks (CNNs) primarily used for?. Text processing. Image generation. Image classification. Time series prediction.

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. Storing the input pixel values. Directly predicting the final output.

What is the purpose of the model catalog in OCI Data Science?. To store, track, share, and manage models. To provide a preinstalled open source library. To deploy models as HTTP endpoints. To create and switch between different environments.

Which capability is supported by Oracle Cloud Infrastructure Language service?. Detecting objects and scenes in images. Converting text into images. Translating text into speech. Analyzing text to extract structured information like sentiment or entities.

What is the role of the self-attention mechanism in a transformer model?. It replaces all previous deep learning techniques for text processing. It assigns different importance to each word in a sequence based on context. It memorizes and retrieves specific words from past training examples. It forces the model to only focus on the most recent words in a sequence.

What is the purpose of Attention Mechanism in Transformer architecture?. Apply a specific function to each word individually. Convert tokens into numerical forms (vectors) that the model can understand. Weigh the importance of different words within a sequence and understand the context. Break down a sentence into smaller pieces called tokens.

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. Prompt Engineering modifies training data, while Fine-tuning alters the model's structure. Prompt Engineering adjusts the model's parameters, while Fine-tuning crafts input prompts. Both involve retraining the model, but Prompt Engineering does it more often.