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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: OCI Generative AI and Oracle 23ai | 10% | - Describe OCI Generative AI Services - Discuss Oracle Vector Search - Discuss Autonomous Database Select AI |
| Topic 2: Intro to Generative AI and LLMs | 15% | - Discuss Generative AI Overview - Explain LLM Fine Tuning - Discuss Large Language Models Fundamentals - Explain Prompt Engineering and Instruction Tuning - Explain Transformers Fundamentals |
| Topic 3: Intro to AI Foundations | 10% | - Discuss AI Basics - Explain AI vs ML vs DL - Discuss AI Applications and Types of Data |
| Topic 4: Intro to OCI AI Services | 20% | - OCI Speech - OCI Language - OCI Document Understanding - OCI Vision |
| Topic 5: Intro to DL Foundations | 15% | - Explain Convolutional Models (CNN) - Discuss Deep Learning Fundamentals - Explain Sequence Models (RNN and LSTM) |
| Topic 6: Get started with OCI AI Portfolio | 15% | - Discuss OCI AI Services Overview - Discuss OCI AI Infrastructure Overview - Discuss OCI ML Services Overview - Explain Responsible AI |
| Topic 7: Intro to ML Foundations | 15% | - Discuss Supervised Learning Fundamentals
- Discuss Unsupervised Learning Fundamentals - Discuss Reinforcement Learning Fundamentals |
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問題 #10
How does AI enhance human efforts?
答案：A
解題說明：
AI enhances human efforts by processing large volumes of data quickly and accurately, performing complex computations that would be time-consuming or impossible for humans to handle manually. This allows humans to focus on more strategic, creative, and decision-making tasks, leveraging AI ' s ability to provide insights, automate repetitive processes, and support decision-making. AI does not physically enhance human capabilities, nor does it replace human workers in all tasks. Instead, it serves as an augmentation tool, amplifying human productivity and capabilities.
問題 #11
In machine learning, what does the term " model training " mean?
答案：A
解題說明：
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.
問題 #12
Lisa is working on a project that involves transcribing thousands of audio files stored in Oracle Cloud. She wants to process multiple files efficiently instead of transcribing them one by one. Which OCI Speech feature should Lisa use?
答案：B
解題說明：
OCI Speech supports batch transcription for efficiently processing prerecorded media. Lisa ' s key requirement is to process thousands of audio files without manually handling them individually. Oracle documentation explicitly identifies OCI Speech as supporting both real-time and batch transcription, while the OCI Speech documentation includes transcription jobs and large batch jobs among its supported workflows.
Oracle Docs Batch support therefore directly addresses high-volume processing of stored audio. Confidence scoring measures the service ' s certainty about recognized speech, timestamping associates transcript content with positions in the source recording, and profanity filtering controls how offensive language is represented.
Those capabilities enhance transcription output but do not provide the required multi-file processing mechanism. Consequently, Batch support is the appropriate OCI Speech capability for scalable transcription of Lisa ' s collection of audio files.
問題 #13
Which feature of OCI Speech helps make transcriptions easier to read and understand?
答案：A
解題說明：
The text normalization feature of OCI Speech helps make transcriptions easier to read and understand by converting spoken language into a more standardized and grammatically correct format. This process includes correcting grammar, punctuation, and formatting, ensuring that the transcribed text is clear, accurate, and suitable for various use cases. Text normalization enhances the usability of transcriptions, making them more accessible and easier to process in downstream applications.
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問題 #14
What is the primary benefit of using the OCI Language service for text analysis?
答案：A
解題說明：
The primary benefit of using the OCI Language service for text analysis is its ability to scale text analysis without requiring users to have extensive machine learning expertise. The service abstracts the complexities of machine learning, allowing businesses to easily process and analyze large amounts of text data through pre- built models. This accessibility makes it possible for a broader range of users to leverage advanced text analysis capabilities, facilitating insights from textual data without needing to develop and train models from scratch.
問題 #15
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