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所在平台: Udemy |
课程主页: https://www.udemy.com/course/1z0-184-25-oracle-ai-vector-search-prof-certification-exam/
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**课程名称:** 1Z0-184-25: Oracle AI Vector Search 专业认证考试 **课程概述:** 本课程旨在帮助您为 Oracle AI Vector Search 专业认证考试做好充分准备。课程内容设计模拟真实考试环境,使用近期考试的真实题目,由经验丰富的团队精心挑选和构建,确保题目内容和难度与考试高度契合。通过练习,您将熟悉考试结构,建立信心,并掌握通过考试所需的专业知识和技能。 **核心内容:* * **向量基础:** 理解向量基本概念,学习使用向量数据类型存储嵌入(embeddings)并进行语义查询。 * **向量距离函数与指标:** 掌握用于 AI 向量搜索的距离函数和度量标准。 * **向量操作:** 学习向量的 DML(数据操作语言)和 DDL(数据定义语言)操作。 * **向量索引:** 学习创建向量索引以加速 AI 向量搜索,并了解 HNSW 和 IVF 向量索引在搜索查询中的应用。 * **相似性搜索:** 掌握精确相似性搜索,以及使用向量索引进行近似相似性搜索,并了解如何进行多向量相似性搜索以实现多文档搜索。 * **向量嵌入:** 学习在 Oracle 数据库内外部生成向量嵌入,并将它们存储在 Oracle 数据库中。 * **构建 RAG 应用:** 理解检索增强生成(RAG)的概念,并学习如何使用 PL/SQL 和 Python 构建 RAG 应用。 * **利用相关 AI 能力:** 探索 Exadata AI Storage 如何加速 AI 向量搜索,使用 Select AI with Autonomous 通过自然语言提示查询数据,以及使用 SQL Loader 和 Oracle Data Pump 加载和卸载向量数据。 **目标:** * 熟练掌握 Oracle AI Vector Search 的各项技术。 * 自信应对并成功通过 1Z0-184-25 专业认证考试。 **学习方式:** 通过大量的模拟真实考题进行练习,充分准备考试。
Prepare to excel in your certification exam with our Real-Time Practice Tests! These tests are thoughtfully designed using authentic questions from recent exams, offering you the most accurate simulation of the actual test environment. My team, with extensive experience in taking these exams, has carefully selected and structured each question to ensure they align perfectly with the exam's content and difficulty level. By working through these practice tests, you'll not only get comfortable with the exam's structure but also build the confidence and expertise required to pass on your very first try. Dive into your preparation today and make exam stress a thing of the past!"Understand Vector FundamentalsUse Vector Data type for storing embeddings and enabling semantic queriesUse Vector Distance Functions and Metrics for AI vector searchPerform DML Operations on VectorsPerform DDL Operations on VectorsUsing Vector IndexesCreate Vector Indexes to speed up AI vector searchUse HNSW Vector Index for search queriesUse IVF Vector Index for search queriesPerforming Similarity SearchPerform Exact Similarity SearchPerform approximate similarity search using Vector IndexesPerform Multi-Vector similarity search for multi-document searchUsing Vector EmbeddingsGenerate Vector Embeddings outside the Oracle databaseGenerate Vector Embeddings inside the Oracle databaseStore Vector Embeddings in Oracle databaseBuilding a RAG ApplicationUnderstand Retrieval-augmented generation (RAG) conceptsCreate a RAG application using PL/SQLCreate a RAG application using PythonLeveraging related AI capabilitiesUse Exadata AI Storage to accelerate AI vector searchUse Select AI with Autonomous to query data using natural language promptsUse SQL Loader for loading vector dataUse Oracle Data Pump for loading and unloading vector data