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所在平台: Udemy |
课程主页: https://www.udemy.com/course/spring-ai-beginner-to-guru/
课程评论：没有评论
课程名称：Spring AI：从初学者到专家 课程概述：传统上，访问人工智能模型，如OpenAI的ChatGPT，一直是Python和JavaScript等编程语言的领域。然而，现在开发者不再受限于这些编程语言。本课程Spring AI专为Java开发者设计，旨在简化人工智能应用程序的开发，降低复杂性。Spring AI项目支持所有主要的人工智能模型，包括OpenAI、Azure OpenAI、Amazon Bedrock、Hugging Face、Ollama、Google Vertex AI（PaLM2和Gemini）、Mistral AI、Anthropic、Watsonx AI等。此外，Spring AI还支持OpenAI和Stability的图像生成AI模型。 课程内容覆盖了以检索增强生成（Retrieval Augmented Generation）为基础的众多应用场景，且课程不要求参与者具备人工智能经验。课程开始时将提供关于人工智能的全面概述，随后通过动手实践开发一个RESTful API来向OpenAI的ChatGPT提问，学习如何指导模型以期返回我们所需格式的数据。 接下来的部分将正式介绍提示工程（Prompt Engineering），集成一系列技术以提升AI模型的响应质量和准确性。课程还将深入探讨检索增强生成（RAG）技术，以帮助大型语言模型获取完成专业任务所需的附加信息。此外，学员将学习如何使用AI创建图像，从文本生成音频文件，以及如何将音频文件转录为文本。 课程更新信息： - 2024年9月9日 - 课程更新至Spring AI 1.0.0-M2 - 2024年10月12日 - 课程更新至Spring AI 1.0.0-M3，Spring Boot 3.3.4 - 2025年1月2日 - 课程更新至Spring AI 1.0.0-M5和Spring Boot 3.3.6 在课程Spring AI：从初学者到专家中学习更多内容，今天就报名吧！
Traditionally accessing Artificial Intelligence Models, such as OpenAI's ChatGPT, has been the domain of programming languages Python and Javascript. Not any more. Spring AI unlocks the power of Generative AI for Java developers. The Spring AI project aims to streamline the development of applications that incorporate artificial intelligence functionality without unnecessary complexity. Spring AI provides support for all major Artificial Intelligence models, including:OpenAIAzure OpenAIAmazon BedrockHuggingFaceOllama Google VertextAI (PaLM2 and Gemini)Mistral AIAntrhopicWatsonxAISpring AI also supports image generation AI models from OpenAI and Stability. Retrieval Augmented Generation is an important use case for dealing with AI models. Spring AI includes robust support for all major Embedding Models and all popular vector databases. No prior experience with AI is needed for this course. You will start the course with a solid overview of what Artificial Intelligence is. Next you'll have a hands on section to develop a RESTful API to ask OpenAI's ChatGPT questions. In this section, you will learn how we can instruct the model to return data in the format we desire. Since no AI experience is required, the next section of the course builds upon what you learned with a formal look at Prompt Engineering. Prompt Engineering is a collection techniques to improve the quality and accuracy of responses from AI Models.Retrieval Augmented Generation (RAG) is an important technique to provide Large Language Models with additional information required to the user's query to complete specialized tasks. You will see how we can use RAG to develop AI experts to perform high specialized tasks. The AI models are not just limited to working with textual information. In this course you will also see how to use AI to create images, create audio files from text, and how to transcribe audio files to text. Course UpdatesSept 9th, 2024 - Course Updated to Spring AI 1.0.0-M2October 12th, 2024 - Course Updated to Spring AI 1.0.0-M3, Spring Boot 3.3.4January 2nd, Course Updated to Spring AI 1.0.0-M5 and Spring Boot 3.3.6Learn all this and more in Spring A:I Beginner to Guru. Enroll today!
