Build Next-Gen LLM Apps with LangChain & LangGraph
About this course
Transform from LLM experimentation to enterprise-grade production with this comprehensive specialization in LangChain and LangGraph development. Master the complete lifecycle of building, deploying, and scaling Large Language Model applications that handle millions of requests with 99.9% uptime. You'll architect resilient microservices, implement parameter-efficient fine-tuning that cuts costs by 90%, and deploy automated CI/CD pipelines with enterprise security controls. Through hands-on labs based on real-world scenarios from e-commerce, healthcare, and finance, you'll learn to decompose monolithic LLM apps into scalable services, validate embeddings for semantic search, and optimize performance achieving sub-100ms response times. The specialization covers critical production concerns including prompt injection protection, chaos engineering for resilience testing, and ROI measurement frameworks that connect model metrics to business value. You'll work with industry-standard tools including Hugging Face Transformers, Docker, Kubernetes, Terraform, and monitoring systems like Prometheus and Grafana. Each course builds practical skills through AI-graded assignments and projects that simulate enterprise constraints around latency, cost, and compliance. By completion, you'll have deployed secure, observable LLM platforms capable of handling enterprise workloads while maintaining cost efficiency and meeting business objectives.
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What you'll learn
- architect resilient microservices for LLM applications
- implement parameter-efficient fine-tuning techniques
- deploy CI/CD pipelines with security controls
- optimize performance to achieve sub-100ms response times
- validate embeddings for semantic search
Course objectives
- transform LLM experimentation into production systems
- prepare applications for enterprise-scale workloads
- understand critical production concerns including prompt injection protection and chaos engineering
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