This course covers advanced concepts and practices for developing production-grade applications using the LangChain framework. Learn to construct sophisticated agentic systems, manage complex conversational memory, optimize data retrieval, implement robust evaluation and monitoring, and deploy scalable, secure LLM solutions. Suitable for engineers aiming to operationalize LangChain projects effectively.
Prerequisites Python & Basic LangChain
Level:
Advanced Architecture
Design and implement complex, multi-step chains and agents using advanced LangChain features.
Memory Management
Select and configure appropriate memory mechanisms for maintaining long-term conversational context.
Data Retrieval Optimization
Architect and optimize retrieval-augmented generation (RAG) pipelines for production scale.
Evaluation and Monitoring
Implement comprehensive evaluation, monitoring, and observability for LangChain applications using tools like LangSmith.
Optimization and Scaling
Apply performance optimization techniques and cost management strategies for LLM applications.
Deployment Strategies
Package, deploy, and scale LangChain applications using containerization and cloud-native technologies.
Security Implementation
Integrate security best practices throughout the LangChain application lifecycle.
© 2026 ApX Machine LearningEngineered with