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所在平台: Udemy |
课程主页: https://www.udemy.com/course/genai-application-architecture/
课程评论：没有评论
课程名称：生成AI应用架构：可扩展与安全的AI设计 课程概述：本课程旨在帮助学员掌握设计和架构可扩展、安全且具有成本效益的生成AI（GenAI）应用的基本技术和最佳实践。学员将深入探讨LGPL架构的原则（层、门、管道和循环），以及这些原则如何应用于使用现代云服务（如AWS）构建GenAI系统。课程内容涵盖负载均衡、容器化、错误处理、监控、日志记录和灾难恢复等关键主题。对于希望了解GenAI架构并确保应用稳健、安全和高效的人士来说，这是一个理想的课程。 学习内容： - 使用LGPL框架架构可扩展和安全的GenAI应用。 - 理解如容器化、负载均衡和灾难恢复等核心概念。 - 学习GenAI系统中的监控、日志记录和错误处理的最佳实践。 - 探索MLOps、持续集成/持续交付（CI/CD）和安全策略，以确保AI应用的可持续性。 本课程专注于构建强大的GenAI系统的架构和原则，提供设计有效AI解决方案所需的知识。立即报名，提升您的GenAI应用架构技能，掌握构建安全、高效和可扩展的GenAI应用的核心最佳实践和技术。准备好提升您的技能了吗？加入我们，一起开始吧！我们在课程中见！
Master the essential techniques and best practices for designing and architecting scalable, secure, and cost-effective Generative AI (GenAI) applications. In this course, you'll explore the principles of the LGPL architecture (Layers, Gates, Pipes, and Loops) and how they apply to building GenAI systems using modern cloud services like AWS. We'll cover critical topics such as load balancing, containerization, error handling, monitoring, logging, and disaster recovery. This course is ideal for those looking to understand GenAI architecture, ensuring applications are resilient, secure, and efficient.What You'll Learn:Architect scalable and secure GenAI applications using the LGPL model.Understand core concepts such as containerization, load balancing, and disaster recovery.Learn best practices for monitoring, logging, and error handling in GenAI systems.Explore MLOps, CI/CD, and security strategies for future-proofing AI applications.This course focuses on the architecture and principles behind building robust GenAI systems, providing the knowledge needed to design effective AI solutions.Enroll now to transform your GenAI Application Architecture skills to the next level. Master GenAI Application Architecture - the core best practices and techniques for building secure, efficient, scalable GenAI Applications.Ready to take your skills to the next level? Join me, and let's get started. See you inside the course!
