LangChain Mastery in 2025 | Full 5 Hour Course [LangChain v0.3]
Skills:
Prompt Systems Engineering90%
The Langchain library is a powerful tool for AI engineering, acting as the foundation of the broader LangChain-ecosystem (that is, LangGraph, LangSmith, LangServe, etc). In this course, you'll learn the fundamentals of building with LLMs and the essentials of LangChain — allowing you to build modern agentic systems and potentially move onto other components in the ecosystem such as LangGraph.
Quick Links!
📌 All Course Material: https://aurelio.ai/course/langchain
⭐ Course Repo: https://github.com/aurelio-labs/langchain-course
🌟 Build Better Agents + RAG:
https://platform.aurelio.ai (use "JBMARCH2025" coupon code for $20 free credits)
This course includes 10 chapters, those are:
1️⃣ When to Use LangChain (https://www.aurelio.ai/learn/langchain-when-to-use)
Guidelines for when we should use LangChain and what problems the framework does and does not solve.
2️⃣ Getting Started with LangChain (https://www.aurelio.ai/learn/langchain-intro)
LangChain is one of the most popular open source libraries for AI Engineers. Here we will introduce the library.
3️⃣ AI Observability with LangSmith (https://www.aurelio.ai/learn/langsmith-intro)
An introduction to LangSmith, an observability service for the LangChain-ecosystem.
4️⃣ Prompt Templating and Techniques in LangChain (https://www.aurelio.ai/learn/langchain-prompts)
Prompting is a critical part of building AI software. Here we'll learn general prompting techniques and specific LangChain tooling for prompting.
5️⃣ Conversational Memory in LangChain (https://www.aurelio.ai/learn/langchain-conversational-memory)
Exploring the various types of conversational memory and best practices for implementing them in LangChain v0.3 and beyond.
6️⃣ Introduction to LangChain Agents (https://www.aurelio.ai/learn/langchain-agents-intro)
An introduction to LangChain's agents in v0.3 and up using both traditional and LCEL syntax.
7️⃣ LangChain Agent Executor Deep Dive (https://www.aurelio.ai/learn/langchain-agent-executor)
A deep dive into
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