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| Section | Weight | Objectives |
|---|---|---|
| OCI Generative AI and Oracle 23ai | 10% | - Describe OCI Generative AI Services - Discuss Autonomous Database Select AI - Discuss Oracle Vector Search |
| Get started with OCI AI Portfolio | 15% | - Discuss OCI AI Infrastructure Overview - Discuss OCI AI Services Overview - Explain Responsible AI - Discuss OCI ML Services Overview |
| Intro to ML Foundations | 15% | - Discuss Reinforcement Learning Fundamentals - Explain Machine Learning Basics - Discuss Supervised Learning Fundamentals
|
| Intro to Generative AI and LLMs | 15% | - Explain Transformers Fundamentals - Explain LLM Fine Tuning - Explain Prompt Engineering and Instruction Tuning - Discuss Large Language Models Fundamentals - Discuss Generative AI Overview |
| Intro to OCI AI Services | 20% | - OCI Language - OCI Speech - OCI Document Understanding - OCI Vision |
| Intro to AI Foundations | 10% | - Discuss AI Applications and Types of Data - Discuss AI Basics - Explain AI vs ML vs DL |
| Intro to DL Foundations | 15% | - Discuss Deep Learning Fundamentals - Explain Sequence Models (RNN and LSTM) - Explain Convolutional Models (CNN) |
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NEW QUESTION # 35
A customer feedback analysis team needs to extract insights from thousands of online product reviews. They want to determine whether customers express positive or negative opinions about different aspects of a product or service. Which feature of OCI Language is helpful?
Answer: D
Explanation:
OCI Language provides pretrained natural language processing capabilities for analyzing unstructured text, including sentiment analysis. In this scenario, the requirement is specifically to determine whether customers express positive or negative opinions concerning individual aspects of a product or service. Oracle ' s OCI Language customer-feedback architecture describes extracting aspects from reviews and associating sentiments such as positive, negative, or neutral with those aspects. Oracle Docs Key phrase extraction identifies important topics or phrases, named entity recognition identifies entities such as organizations, people, or locations, and language detection determines the language in which content is written. None directly evaluates customer opinion. Sentiment analysis therefore precisely matches the business requirement because it transforms subjective review content into structured sentiment information that can be analyzed at scale.
NEW QUESTION # 36
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?
Answer: C
Explanation:
The primary advantage of using dedicated AI clusters in the Oracle Cloud Infrastructure (OCI) Generative AI service is the provision of high-performance compute resources that are specifically optimized for fine-tuning tasks. Fine-tuning is a critical step in the process of adapting pre-trained models to specific tasks, and it requires significant computational power. Dedicated AI clusters in OCI are designed to deliver the necessary performance and scalability to handle the intense workloads associated with fine-tuning large language models (LLMs) and other AI models, ensuring faster processing and more efficient training.
NEW QUESTION # 37
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?
Answer: B
NEW QUESTION # 38
Which feature is NOT available as part of OCI Speech capabilities?
Answer: A
Explanation:
OCI Speech capabilities are designed to be user-friendly and do not require extensive data science experience to operate. The service provides features such as transcribing audio and video files into text, offering grammatically accurate transcriptions, supporting multiple languages, and providing timestamped outputs.
These capabilities are built to be accessible to a broad range of users, making speech-to-text conversion seamless and straightforward without the need for deep technical expertise.
NEW QUESTION # 39
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?
Answer: B
Explanation:
Oracle Cloud Infrastructure Supercluster is designed to deliver exceptional performance and scalability for complex AI tasks. The primary benefit of this infrastructure is its ability to handle demanding AI workloads, offering high-performance computing (HPC) capabilities that are crucial for training large-scale AI models and processing massive datasets. The architecture of the Supercluster ensures low-latency networking, efficient resource allocation, and high-throughput processing, making it ideal for AI tasks that require significant computational power, such as deep learning, data analytics, and large-scale simulations.
NEW QUESTION # 40
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