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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Foundations | 10% | - Artificial Intelligence basics and terminology
|
| Topic 2: Generative AI and Large Language Models | 15% | - Generative AI concepts
|
| Topic 3: OCI Generative AI and Oracle 23ai | 10% | - OCI Generative AI Service features
|
| Topic 4: Deep Learning Foundations | 15% | - Deep Learning and neural networks
|
| Topic 5: Introduction to OCI AI Services | 20% | - OCI AI Service APIs
|
| Topic 6: Machine Learning Foundations | 15% | - Machine Learning fundamentals
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| Topic 7: OCI AI Portfolio | 15% | - Overview of OCI AI offerings
|
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質問 # 10
You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?
正解：D
解説：
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.
質問 # 11
What is the key feature of Recurrent Neural Networks (RNNs)?
正解：B
解説：
Recurrent Neural Networks (RNNs) are a class of neural networks where connections between nodes can form cycles. This cycle creates a feedback loop that allows the network to maintain an internal state or memory, which persists across different time steps. This is the key feature of RNNs that distinguishes them from other neural networks, such as feedforward neural networks that process inputs in one direction only and do not have internal states.
RNNs are particularly useful for tasks where context or sequential information is important, such as in language modeling, time-series prediction, and speech recognition. The ability to retain information from previous inputs enables RNNs to make more informed predictions based on the entire sequence of data, not just the current input.
In contrast:
* Option A (They process data in parallel) is incorrect because RNNs typically process data sequentially, not in parallel.
* Option B (They are primarily used for image recognition tasks) is incorrect because image recognition is more commonly associated with Convolutional Neural Networks (CNNs), not RNNs.
* Option D (They do not have an internal state) is incorrect because having an internal state is a defining characteristic of RNNs.
This feedback loop is fundamental to the operation of RNNs and allows them to handle sequences of data effectively by " remembering " past inputs to influence future outputs. This memory capability is what makes RNNs powerful for applications that involve sequential or time-dependent data.
質問 # 12
Which capability is supported by the Oracle Cloud Infrastructure Vision service?
正解：A
解説：
The Oracle Cloud Infrastructure (OCI) Vision service is designed for image analysis tasks, which includes the capability to detect and recognize objects, such as vehicle number plates. This functionality is particularly useful for applications such as automated enforcement of traffic laws, where the system can identify vehicles exceeding speed limits and issue citations based on the detected number plates. This capability leverages advanced computer vision techniques to process and analyze visual data, making it suitable for applications in public safety, transportation, and law enforcement.
質問 # 13
What feature of OCI Data Science provides an interactive coding environment for building and training models?
正解：B
解説：
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.
質問 # 14
Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?
正解：C
解説：
Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.
質問 # 15
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