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所在平台: Udemy |
课程主页: https://www.udemy.com/course/mastering-azure-openai-from-zero-to-hero/
课程评论：没有评论
课程总结：Azure Generative（OpenAI）与预测人工智能（23+小时） 本课程专为有意学习“Microsoft Azure OpenAI服务”的学员设计，关注Azure OpenAI的核心概念。课程内容涵盖了从基本的函数调用到更复杂的令牌处理等多方面的知识。你将学习温度参数、令牌参数、如何将外部API整合进Azure OpenAI函数调用以及将其他Azure服务（如Azure语音服务）与Azure OpenAI结合，以提升你的引擎或模型的效率和能力。 课程内容被精简，以提供重要的知识，让你的学习时间更具价值。虽然课程时间短，但承诺能提供物有所值的学习体验，帮助你成为Azure OpenAI及其各种功能的专家。课程适合所有水平的学习者，基础概念也会详细讲解。 此外，课程包含了丰富的实践实验，你将获得一个GitHub资源库，里面包含与课程相关的所有代码。实践实验涵盖多个主题，包括： 1) 聊天完成API； 2) 使用文本嵌入引擎增强机器学习过程； 3) 将语音转文本的令牌查询检索集成到聊天引擎中； 4) 使用Azure OpenAI独有的函数调用功能调用外部API以获取实时信息/数据； 5) 通过将Azure AI搜索与聊天引擎结合，探索RAG（检索增强生成）的概念； 6) 使用Azure机器学习工作区进行向量搜索和信息检索； 7) 利用计算机视觉使用GPT-4。 课程还包含一个奖金部分，介绍了GitHub Copilot的相关概念，如多语言支持、@VScode代理、@工作区代理及代码调试等。 课程的先修知识要求是对Python编程语言和基本命令行操作的了解。购买本课程，准备好开始一段精彩的学习旅程吧！
NOTE: This course is only for people interested in learning "Microsoft Azure OpenAI service". If you are looking for open source version of OpenAI, then this course should not be on your wish list.This course covers all the key concepts related to Azure OpenAI. Be it function calling or something as small as knowing how your engine processes tokens, the course has it all covered. In this course you will learn about concepts such as temperature parameter, token parameter, adding external API's to Azure Open AI function calling, integrating other Azure services such as the Azure Speech Service with Azure Open AI to make your engine/ model more efficient and powerful. This course is tailored in a very concise and short manner, providing you with only the important stuff so that your time is well-spent. This course will act as a bridge to your journey in being a master at using Azure Open AI and its offerings. Although this course is short, the course assures that you get your money's worthCourse Level: The course goes all the way up from level 0 to level 100; Don't know what's the basic difference between Azure OpenAI and OpenAI, don't worry, the course's got your back.Hand-On Labs: The hands-on labs in the course are very enriching. You will be provided with a github repository which will contain all the codes for the hands-on labs covered in this course. The hands-on labs offered in this course cover a variety of topics including:1) Chat Completions API.2) Making use of text embedding engine for enhanced machine learning processes.3) integrating speech-to-text token query retrieval in your chat engine.4) making use of function calling functionality exclusive to Azure Open Ai to call an external API to retrieve real-time information/data.5) Exploring concept of RAG (Retrieval Augmented Generation) by integrating Azure Ai Search with your chat engine.6) Using Vector search and information retrieval using Azure Machine Learning Workspace.7) Using GPT-4 using Computer Vision.Bonus Section: A bonus section that includes GitHub Copilot has been made available with this course as well. Concepts like multi language support, @VScode agent, @workspace agent and code debugging have been explained in depth.Prerequisites: knowledge about Python programming language and basic command line interface commands makes up for the prerequisites for the course.Buy this course and get ready to embark on a journey full of brilliant learning.
