Automate & Secure LLM Deployments

本课程是 Build Next-Gen LLM Apps with LangChain & LangGraph 专项课程的一部分

位教师：Starweaver

访问权限由 New York State Department of Labor 提供

3个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

3个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Design automated CI/CD pipelines for LLM deployments using containerization and infrastructure as code.
Apply security best practices including API protection, prompt injection prevention, and compliance frameworks.
Configure production monitoring, auto-scaling, and cost optimization for enterprise LLM systems.

您将获得的技能

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

1 项作业

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Build Next-Gen LLM Apps with LangChain & LangGraph 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有3个模块

Every day, companies waste thousands of dollars on poorly deployed LLM applications—experiencing downtime, security breaches, and runaway costs that could have been prevented. This comprehensive course teaches you to build automated CI/CD pipelines specifically designed for LLM applications, implement enterprise-grade security controls, and optimize for scale and cost. Through hands-on labs based on real-world scenarios, you'll work with Docker, Kubernetes, Terraform, and cloud platforms to build production-ready systems. Each module includes practical exercises where you'll solve actual deployment challenges faced by companies scaling LLM applications.

For DevOps, platform, and AI engineers deploying and operating large-scale LLM systems, with a focus on automation, security, cost optimization, and building reliable, high-performance AI platforms. Learners should have a basic understanding of Docker, APIs, and cloud platforms. Familiarity with CI/CD, Python, and basic security practices is helpful but not required. By course completion, you'll have deployed a secure, scalable LLM platform capable of handling millions of requests while maintaining 99.9% uptime. Perfect for DevOps engineers, platform engineers, and technical professionals ready to operationalize LLM applications.

Build automated CI/CD pipelines for LLM applications using GitHub Actions, Docker containerization, and blue-green deployment strategies. You'll configure workflows that automatically build container images, scan them for vulnerabilities, and deploy them with zero downtime. Through hands-on practice, you'll transform manual deployment processes into reliable automation that builds, scans, pushes, and blue-green deploys LLM applications to production environments.

涵盖的内容

4个视频2篇阅读材料1次同伴评审

4个视频总计35分钟

Welcome to Automated LLM Deployments 4分钟
Introduction to LLM CI/CD Pipelines 10分钟
Containerizing LLM Applications with Docker 8分钟
Infrastructure as Code for LLM Deployments 14分钟

2篇阅读材料总计10分钟

Welcome to the Course: Course Overview 5分钟
MLOps Best Practices Guide 5分钟

1次同伴评审总计20分钟

Hands-On-Learning: Automate LLM Pipeline: Deploy TechCorp's Multi-Model Infrastructure 20分钟

Implement comprehensive security controls for production LLM APIs using identity and access management, secret management, and automated security scanning. You'll configure least-privilege IAM roles, set up secure secret ARNs for API keys and credentials, and run Trivy scans to confirm zero critical security findings. The module covers LLM-specific security concerns including prompt injection prevention, rate limiting, and audit logging for compliance requirements

涵盖的内容

3个视频1篇阅读材料1次同伴评审

Ensure production reliability and cost efficiency by implementing comprehensive monitoring, automated rollback strategies, and cost optimization techniques for LLM systems. You'll create CloudWatch alarms to track critical metrics, simulate latency spikes to verify automated rollback rules, and configure auto-scaling policies that handle traffic variations. The module also covers cost optimization strategies including response caching, intelligent model routing, and resource management to reduce operational expenses

涵盖的内容

4个视频1篇阅读材料1个作业2次同伴评审

4个视频总计42分钟

Monitoring LLM Performance and Costs 10分钟
Auto-scaling Strategies for LLM Services 14分钟
Cost Optimization Techniques 15分钟
Next Steps in LLM Operations 4分钟

1篇阅读材料总计5分钟

Production LLM Monitoring Guide 5分钟

1个作业总计20分钟

Automate & Secure LLM Deployments 20分钟

2次同伴评审总计80分钟

Hands-On-Learning: Scale to Million Users: Optimize GlobalAI's Production System 20分钟
Project: Deploy Production LLM Platform: TechUnicorn's Enterprise Solution 60分钟