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| Section | Weight | Objectives |
|---|---|---|
| Intro to AI Foundations | 10% | - Discuss AI Applications and Types of Data - Discuss AI Basics - Explain AI vs ML vs DL |
| OCI Generative AI and Oracle 23ai | 10% | - Describe OCI Generative AI Services - Discuss Oracle Vector Search - Discuss Autonomous Database Select AI |
| Intro to DL Foundations | 15% | - Discuss Deep Learning Fundamentals - Explain Convolutional Models (CNN) - Explain Sequence Models (RNN and LSTM) |
| Get started with OCI AI Portfolio | 15% | - Discuss OCI ML Services Overview - Discuss OCI AI Infrastructure Overview - Explain Responsible AI - Discuss OCI AI Services Overview |
| Intro to ML Foundations | 15% | - Explain Machine Learning Basics - Discuss Reinforcement Learning Fundamentals - Discuss Supervised Learning Fundamentals
|
| Intro to Generative AI and LLMs | 15% | - Explain Prompt Engineering and Instruction Tuning - Explain LLM Fine Tuning - Discuss Generative AI Overview - Discuss Large Language Models Fundamentals - Explain Transformers Fundamentals |
| Intro to OCI AI Services | 20% | - OCI Document Understanding - OCI Speech - OCI Vision - OCI Language |
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NEW QUESTION # 11
What key objective does machine learning strive to achieve?
Answer: D
Explanation:
The key objective of machine learning is to enable computers to learn from experience and improve their performance on specific tasks over time. This is achieved through the development of algorithms that can learn patterns from data and make decisions or predictions without being explicitly programmed for each task.
As the model processes more data, it becomes better at understanding the underlying patterns and relationships, leading to more accurate and efficient outcomes.
NEW QUESTION # 12
You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?
Answer: B
Explanation:
For automating transcription tasks in a medical transcription team, the most appropriate OCI AI service to use would be the " Speech " service. This service is designed to convert spoken language into text, which is essential for transcribing spoken medical reports or consultations into written form. The OCI Speech service provides capabilities such as speech-to-text conversion, which is specifically tailored for handling audio input and producing accurate transcriptions.
NEW QUESTION # 13
What feature of OCI Data Science provides an interactive coding environment for building and training models?
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 # 14
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?
Answer: A
Explanation:
In this healthcare scenario, where the goal is to classify patients into three categories-Low Risk, Moderate Risk, and High Risk-based on their medical history and vital signs, a Multi-Class Classification algorithm is required. Multi-class classification is a type of supervised learning algorithm used when there are three or more classes or categories to predict. This method is well-suited for situations where each instance needs to be classified into one of several categories, which aligns with the requirement to categorize patients into different risk levels.
NEW QUESTION # 15
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?
Answer: A
Explanation:
The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI ' s OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.
NEW QUESTION # 16
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