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| Section | Weight | Objectives |
|---|---|---|
| Intro to DL Foundations | 15% | - Explain Convolutional Models (CNN) - Explain Sequence Models (RNN and LSTM) - Discuss Deep Learning Fundamentals |
| Intro to ML Foundations | 15% | - Discuss Reinforcement Learning Fundamentals - Discuss Unsupervised Learning Fundamentals - Discuss Supervised Learning Fundamentals
|
| Intro to AI Foundations | 10% | - Discuss AI Applications and Types of Data - Explain AI vs ML vs DL - Discuss AI Basics |
| Intro to Generative AI and LLMs | 15% | - Discuss Generative AI Overview - Explain Prompt Engineering and Instruction Tuning - Explain Transformers Fundamentals - Discuss Large Language Models Fundamentals - Explain LLM Fine Tuning |
| Get started with OCI AI Portfolio | 15% | - Discuss OCI ML Services Overview - Discuss OCI AI Infrastructure Overview - Discuss OCI AI Services Overview - Explain Responsible AI |
| Intro to OCI AI Services | 20% | - OCI Document Understanding - OCI Language - OCI Vision - OCI Speech |
| OCI Generative AI and Oracle 23ai | 10% | - Discuss Autonomous Database Select AI - Describe OCI Generative AI Services - Discuss Oracle Vector Search |
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NEW QUESTION # 38
In machine learning, what does the term " model training " mean?
Answer: D
Explanation:
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.
NEW QUESTION # 39
Which AI domain can be employed for identifying patterns in images and extract relevant features?
Answer: B
Explanation:
Computer Vision is the AI domain specifically employed for identifying patterns in images and extracting relevant features. This field focuses on enabling machines to interpret and understand visual information from the world, automating tasks that the human visual system can perform, such as recognizing objects, analyzing scenes, and detecting anomalies. Techniques in Computer Vision are widely used in applications ranging from facial recognition and image classification to medical image analysis and autonomous vehicles.
NEW QUESTION # 40
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 finds that the model still uses outdated information. Which approach should Emma use instead?
Answer: B
Explanation:
Retrieval-Augmented Generation is the appropriate approach when a chatbot must answer using information that changes frequently. Oracle defines RAG as a technique that retrieves information from specific external data sources and augments an LLM ' s response with that retrieved context, producing grounded answers.
Oracle Docs Oracle further explains that RAG can incorporate information that is more current than the model
' s original training data and that knowledge repositories can be continually updated without retraining the underlying LLM. Oracle Docs Fine-tuning is better suited to adapting model behavior or specialization, not continuously changing factual information. Prompt engineering and zero-shot prompting control how instructions are presented but do not independently supply current return-policy data. Therefore, RAG is the correct solution for providing accurate, current, organization-specific policy responses.
NEW QUESTION # 41
How does Oracle Cloud Infrastructure Document Understanding service facilitate business processes?
Answer: A
Explanation:
Oracle Cloud Infrastructure (OCI) Document Understanding service facilitates business processes by automating data extraction from documents. This service leverages machine learning to identify, classify, and extract relevant information from various document types, reducing the need for manual data entry and improving efficiency in document processing workflows. Automation of these tasks enables organizations to streamline operations and reduce errors associated with manual data handling.
NEW QUESTION # 42
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 # 43
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