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.
LangChain Learning Path
Build a traceable LangChain application with typed composition, retrieval, tools, evaluation, and production controls.
- Compose prompts, models, parsers, and runnables
- Add retrieval, tools, memory boundaries, and streaming
- Evaluate, trace, secure, optimize, and deploy
Evidence-Grounded Policy Assistant
Build a RAG assistant that retrieves policy evidence, cites sources, uses a bounded escalation tool, and is evaluated for groundedness.
Milestones
- Create ingestion, chunking, retrieval, and typed answer chain
- Add escalation tool, trace metadata, and safe failure behavior
- Run retrieval and answer evaluation datasets
Completion Evidence
- Evaluation results
- Trace samples
- Cost and latency profile
Open the complete project guide
Evidence-Grounded Policy Assistant Readiness Check
Complete each criterion and retain the listed evidence before marking the course capstone ready for review.
0 of 6 criteria complete
Self-assessment
Complete every milestone and evidence item to pass this readiness gate.
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
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4. Runnables & LCEL
Lesson
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5. Embeddings & Vector Stores
Lesson
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6. RAG & Retrieval
Lesson
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7. Conversational RAG
Lesson
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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
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LangChain Topic Hub
Use the full topic workspace when you want tutorials, practice, interview prep, and nearby topic links in one place.
Open LangChain topic hub
Tutorials, practice, and prep together
Topic hub
4 surfaces
Runnables and prompts
Retrieval and RAG
Learn model pipelines, prompts, structured output, retrieval, tools, agents, streaming, evaluation, and production safeguards through a focused application path.
LangChain Benefits
- 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.