LangChain Tutorial
Build Production AI Apps with LangChain
Master LangChain for production LLM applications with prompts, models, LCEL, RAG, agents, memory, streaming, evaluation, and deployment patterns.
14Topics
30+Examples
FreeAlways
About LangChain
Master LangChain for production LLM applications with prompts, models, LCEL, RAG, agents, memory, streaming, evaluation, and deployment patterns.
Prerequisites
Basic computer knowledge is enough to start. Prior programming experience is helpful but not required.
Audience
Designed for beginners, students, interview preparation, and developers who want a clear LangChain path.
What You'll Learn
Core concepts, examples, common mistakes, practical patterns, FAQs, and a step-by-step learning roadmap.
Tools Needed
Use a modern browser, code editor, terminal, and the available online compiler when supported.
Tutorial Topics
Follow the lessons in order, or jump straight into the topic you need.
Open this lesson in the LangChain tutorial path.
Open this lesson in the LangChain tutorial path.
3. Prompts & Parsers
Lesson
Open this lesson in the LangChain tutorial path.
4. Runnables & LCEL
Lesson
Open this lesson in the LangChain tutorial path.
5. Embeddings & Vector Stores
Lesson
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6. RAG & Retrieval
Lesson
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7. Conversational RAG
Lesson
Open this lesson in the LangChain tutorial path.
Open this lesson in the LangChain tutorial path.
9. LangGraph Workflows
Lesson
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10. Memory & State
Lesson
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11. Async, Streaming & Batch
Lesson
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12. Security & Guardrails
Lesson
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13. Production & Evaluation
Lesson
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14. Capstone Project
Lesson
Open this lesson in the LangChain tutorial path.
Why Learn LangChain?
- Build a strong foundation with clear explanations and examples.
- Practice concepts in a structured order instead of jumping randomly.
- Prepare for interviews with common mistakes, FAQs, and practical notes.
- Learn patterns that transfer to real projects and production work.
- Use one complete learning path from basics to advanced topics.
