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所在平台: Udemy |
课程主页: https://www.udemy.com/course/dspy-learn-how-to-program-not-prompt-language-models/
课程评论：没有评论
课程名称：DSPy：学习如何编程（而非提示）语言模型 课程概述：在本教程中，我将向您介绍DSPy，一个强大的框架，用于编程（而不是提示）语言模型。我们将探索DSPy如何帮助您构建大语言模型应用程序，并减少手动提示优化的需求。我将解释签名和模块的概念，以及它们如何用于定义应用程序的输入、输出和流程。此外，我还将演示如何利用数据集进行提示优化。整个教程中，我们将通过实际编码示例进行实践，包括构建股票分析工具、国际象棋玩家代理以及BabyAGI，一个自主任务驱动的人工智能代理。欢迎加入我，一起来了解DSPy及其令人兴奋的功能！ 课程对象：本课程特别设计了两个主要学习群体： 1. 渴望了解人工智能和提示优化的Python开发人员：如果您拥有扎实的Python编程基础，并希望将专业知识扩展到人工智能这一激动人心的领域，本课程将为您提供必要的实践技能和理论知识，帮助您表现出色。特别适合希望利用人工智能进行自动化过程的开发者，尤其是在优化与AI模型有效交互的提示方面。无论您是希望增强现有项目还是探索人工智能的新机会，本课程都将为您提供前沿的AI应用开发技能。 2. 对手动提示优化感到厌倦的AI工程师：对于那些觉得手动提示优化繁琐且耗时的AI专业人士，本课程将深入探讨自动化解决方案。学习如何实施先进技术，以简化工作流程并提高AI系统的效率和效果。本课程将教您如何使用Python来自动化和优化提示的过程，使您能够专注于AI工程的更战略性方面。 您将获得的收益： 在课程结束时，学习者将能够： - 理解人工智能和提示优化的原理和方法。 - 应用Python编程技能来自动化和优化AI模型的提示。 - 通过减少手动输入调整的需求来提升AI系统的效率。 - 在项目或角色中通过整合先进的AI技术进行创新。
In this tutorial, I will introduce you to DSPy, a powerful framework for programming (not prompting) language models. We will explore how DSPy can help you build LLM applications by reducing the need for manual prompt optimization. I will explain the concept of signatures and modules, and how they can be used to define the input, outputs, and flow of your application. Additionally, I will demonstrate how DSPy allows for prompt optimization using data sets. Throughout the tutorial, we will work on practical coding examples, including building a stock analysis tool, a chess playing agent, and BabyAGI, an autonomous task-based AI agent. Join me to learn more about DSPy and its exciting features!This course is specifically designed for two main groups of learners:Python Developers Eager to Learn About AI and Prompt Optimization:If you have a solid foundation in Python programming and are looking to expand your expertise into the exciting field of artificial intelligence, this course will provide you with the practical skills and theoretical knowledge necessary to excel. This course is ideal for developers who are interested in understanding how to leverage AI for automated processes, specifically in optimizing prompts to interact effectively with AI models. Whether you aim to enhance your current projects or want to explore new opportunities in AI, this course will equip you with cutting-edge skills in AI application development.AI Engineers Tired of Manual Prompt Optimization:For AI professionals who find the task of manual prompt optimization tedious and time-consuming, this course offers a deep dive into automated solutions. Learn how to implement advanced techniques that streamline your workflow and improve the efficiency and effectiveness of your AI systems. This course will teach you how to use Python to automate and refine the process of prompt optimization, enabling you to focus on more strategic aspects of AI engineering.What Will You Gain?By the end of this course, learners will be able to:Understand the principles and methodologies behind AI and prompt optimization.Apply Python programming skills to automate and optimize prompts for AI models.Enhance AI system efficiencies by reducing the need for manual input adjustments.Innovate within their projects or roles by incorporating advanced AI techniques.
