Creation of Agents using Langchain and Langgraph
Build the next generation of intelligent, autonomous systems. Master the industry-standard open-source frameworks for creating sophisticated, stateful AI agents that reason, act, and collaborate.
This expert-level course from TrulyAcademic is designed for software engineers, ML practitioners, and AI developers who want to move beyond API calls and simple chatbots. Dive deep into the LangChain and LangGraph ecosystems to architect, code, and deploy robust production-grade AI agents. Learn to stitch together language models, tools, memory, and control flow to create applications that perform complex, multi-step tasks with autonomy and precision.
Key Highlights of This Course:
Foundational to Advanced Mastery: Begin with core LangChain Components (Models, Prompts, Chains, Agents, Memory) and rapidly advance to building complex, stateful workflows with LangGraph for production-level control and reliability.
Architect Stateful Agent Systems: Go beyond simple agents. Learn to design and implement persistent, multi-session agents with built-in memory, contextual awareness, and the ability to manage long-running, iterative processes using LangGraph’s graph-based state machines.
Hands-On with the Full Stack: Gain practical experience integrating a variety of tools and data sources. Work with OpenAI, Anthropic Claude, and open-source LLMs via Ollama. Connect to vector databases (ChromaDB, Pinecone), APIs, and computational tools like Python REPL.
Master LangGraph for Complex Workflows: Deep dive into LangGraph to create cyclic, recursive, and conditional agent workflows. Implement human-in-the-loop checkpoints, supervised agentic reasoning, and sophisticated error handling and tracing within your agent graphs.
Build Multi-Agent Teams & Swarms: Engineer systems where multiple specialized agents (e.g., Planner, Researcher, Coder, Critic) collaborate, debate, and coordinate to solve problems beyond the capability of a single agent, simulating real-world organizational dynamics.
Tool Creation & Advanced RAG: Move beyond pre-built tools. Learn to craft custom tools and functions for your agents. Implement Advanced Retrieval-Augmented Generation (RAG) with query routing, multi-retrieval, and agentic document interrogation for superior knowledge grounding.
Production-Ready Deployment: Focus on the engineering essentials: debugging, observability (with LangSmith), evaluating agent performance, and deploying your agentic applications as scalable APIs or services using modern frameworks.
Real-World Capstone Projects: Apply your knowledge to build sophisticated agents, such as an Autonomous Research Assistant, a Debugging & Code Review Agent, or a Dynamic Customer Support Orchestrator. Graduate with a portfolio of demonstrable, complex agent systems.
Open-Source & Framework-Agnostic Skills: Develop transferable skills in agentic design patterns and orchestration logic. While focused on LangChain, the principles empower you to work with other frameworks, making you a versatile AI engineer.
Expert-Led, Code-Intensive Learning: Learn directly from practitioners building agent systems at scale. The curriculum is centered on live coding, code reviews, and best practices for maintainable, efficient agent codebases.