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.
Automate & Secure LLM Deployments
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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.
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最近已更新！
December 2025
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
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
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
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
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