Build Next-Gen LLM Apps with LangChain & LangGraph

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

• Build and deploy production-grade LLM applications using LangChain and microservices architecture
• Implement fine-tuning, embeddings validation, and performance optimization to achieve 99.9% uptime and reduce costs by 90%
• Design monitoring, chaos testing, and ROI frameworks linking LLM performance to business value

• Basic familiarity with the topic and common terminology
• Readiness to practice through applied exercises or case-based work