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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-local-llm-applications-using-python-and-ollama/
课程评论：没有评论
课程名称：使用Python和Ollama构建本地LLM应用程序 课程概述：如果您是一位开发者、数据科学家或人工智能爱好者，希望在本地系统上构建和运行大型语言模型（LLMs），那么本课程将非常适合您。您是否希望在不将数据发送到云端的情况下利用LLMs的强大功能？您是否在寻找能够利用Python、Ollama和LangChain等强大工具的安全、私密解决方案？本课程将教您如何在自己的机器上构建安全且功能完善的LLM应用程序。 在本课程中，您将学习： - 设置Ollama并下载可供本地使用的Llama LLM模型。 - 使用命令行工具自定义模型并保存修改版本。 - 基于Python开发LLM应用程序，全面掌控您的模型。 - 使用Ollama的Rest API将模型集成到您的应用程序中。 - 利用LangChain构建增强检索生成（RAG）系统，以实现高效的文档处理。 - 创建端到端的LLM应用程序，使用LangChain和Ollama的强大功能精准回答用户问题。 为什么要构建本地LLM应用程序？本地应用程序确保完全的数据隐私——您的数据永远不会离开您的系统。此外，运行模型的灵活性和可定制性使您可以完全掌控，而无需依赖云服务。 在整个课程中，您将使用Python构建、自定义和部署模型，并实施提示工程、检索技术和模型集成等关键功能——这一切都是在您本地环境中进行的。 本课程的独特之处在于其对隐私、控制以及使用前沿工具（如Ollama和LangChain）进行实践体验的重视。到课程结束时，您将拥有一个功能齐全的LLM应用程序及在自己的基础上构建安全AI系统所需的技能。 准备好构建您自己的私有LLM应用程序了吗？立即注册，开始学习！
If you are a developer, data scientist, or AI enthusiast who wants to build and run large language models (LLMs) locally on your system, this course is for you. Do you want to harness the power of LLMs without sending your data to the cloud? Are you looking for secure, private solutions that leverage powerful tools like Python, Ollama, and LangChain? This course will show you how to build secure and fully functional LLM applications right on your own machine.In this course, you will:Set up Ollama and download the Llama LLM model for local use.Customize models and save modified versions using command-line tools.Develop Python-based LLM applications with Ollama for total control over your models.Use Ollama's Rest API to integrate models into your applications.Leverage LangChain to build Retrieval-Augmented Generation (RAG) systems for efficient document processing.Create end-to-end LLM applications that answer user questions with precision using the power of LangChain and Ollama.Why build local LLM applications? For one, local applications ensure complete data privacy-your data never leaves your system. Additionally, the flexibility and customization of running models locally means you are in total control, without the need for cloud dependencies.Throughout the course, you'll build, customize, and deploy models using Python, and implement key features like prompt engineering, retrieval techniques, and model integration-all within the comfort of your local setup.What sets this course apart is its focus on privacy, control, and hands-on experience using cutting-edge tools like Ollama and LangChain. By the end, you'll have a fully functioning LLM application and the skills to build secure AI systems on your own.Ready to build your own private LLM applications? Enroll now and get started!
