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所在平台: Udemy |
课程主页: https://www.udemy.com/course/agno-agentic-ai-with-mcp/
课程评论：没有评论
课程名称：Agno Agentic AI与MCP协议 课程概述：本课程旨在帮助学员解锁Agentic AI的力量，采用实践为主的方式教授如何使用Agno Agentic框架和MCP（模型上下文协议）构建智能金融代理。无论您是AI爱好者、开发者，还是金融科技创新者，这门课程将通过实际项目帮助您理解AI工作流的下一次进化。您将深入了解Agno如何简化以目标为导向的自主智能代理的开发，使用结构化的规划和沟通模式。学习设计能够分析市场数据、执行任务并使用记忆代理进行知识保留的金融代理。探索Agno Playground，这是一个可视化环境，用于测试和模拟具有动态提示和任务流的代理。 课程强调多代理协作，代理之间能够沟通并协调，团队合作解决复杂问题。通过真实的金融案例，您将创建不仅能独立行动，还能在多代理环境中进行计划、反思和委派的代理。 您将构建的内容包括： - 使用Agno和MCP的智能金融分析代理，具有回忆和推理能力的记忆增强代理 - 一个多代理系统，其中代理协同完成金融任务 - 使用Agno Playground模拟和可视化工作流 本课程不要求有代理框架的前期经验，只需具备基本的Python编程和AI概念理解。今天就开始您的Agentic AI之旅，构建能够自主思考、规划和行动的系统！
Unlock the power of Agentic AI with this focused, hands-on course designed to teach you how to build intelligent financial agents using the Agno Agentic Framework and the MCP (Model context Protocol ). Whether you're an AI enthusiast, developer, or a financial tech innovator, this course will help you grasp the next evolution of AI workflows through practical projects.You'll dive into how Agno simplifies the development of autonomous, goal-driven agents using structured planning and communication patterns. Learn to design financial agents that can analyze market data, execute tasks, and retain knowledge using Memory Agents. Explore the Agno Playground, a visual environment to test and simulate agents with dynamic prompts and task flows.The course emphasizes multi-agent collaboration where agents communicate and coordinate as teams to solve complex problems. Using real-world financial use cases, you'll create agents that not only act independently but also plan, reflect, and delegate in multi-agent environments.What you'll build:A smart Financial Analyst Agent using Agno & MCPA Memory-augmented agent capable of recall and reasoningA Multi-Agent system where agents collaborate on financial tasksUse of Agno Playground to simulate and visualize workflowsNo prior experience in agent frameworks is required-just a basic understanding of Python and AI concepts.Start your journey into the world of Agentic AI today and build systems that think, plan, and act-autonomously.
