Learn LangChain: AI & RAG
55 days old
Not in any tracked top chart right now.
Updated 27 Sep 2026 · rankings refresh through the day
DeveloperShahbaz Khan
CategoryEducation
Price4.99 CAD
Released
Rating★ 0.0 (0)
Version1.0
Age rating9+
First seen by us
25 Sep 2026
Rating
0.0 ★
0 ratings
Measured
Learn LangChain: AI & RAG on the App Store
App details
App ID
6794570808
Publisher
Shahbaz Khan
Content rating
9+
Where it ranks now
Every top chart it appears in across 24 countries.
| Country | Charts | Rank |
|---|---|---|
| Not charting right now. | ||
Ratings
App Store, worldwide.
Rating
0.0 ★
0 ratings
Measured
Ratings
0
Measured
About Learn LangChain: AI & RAG
Learn LangChain and build modern AI applications with practical, structured lessons.Learn how large language model apps work—from prompt templates and chat models to chains, agents, retrieval-augmented generation, and production deployment.
Whether you are beginning with LangChain or expanding your LLM engineering skills, Learn LangChain helps you study the concepts and patterns used to build real AI products.
WHAT YOU’LL LEARN
- LangChain fundamentals and setup
- LLMs, chat models, prompts, and structured output
- LCEL and composable application chains
- Memory, conversation workflows, and state
- Document loaders, text splitters, embeddings, and vector stores
- Retrieval-augmented generation, or RAG
- Advanced RAG patterns, including Graph RAG and Agentic RAG
- AI agents, tools, ReAct workflows, and multi-agent systems
- LangGraph concepts, nodes, state, and workflows
- LangSmith, LangServe, templates, observability, and debugging
- Vector databases, semantic search, and retrieval pipelines
- AI evaluation, testing, quality measurement, and RAG evaluation
- Streaming, caching, error handling, scaling, and production architecture
- LoRA and efficient LLM fine-tuning
- vLLM, model serving, inference, and deployment concepts
- CrewAI and modern multi-agent application patterns
- MCP concepts and connected AI workflows
BUILD HANDS-ON PROJECTS
Apply what you learn through practical projects, including:
- Q&A bots with RAG
- Multi-document research agents
- AI customer support systems
- Vector search and retrieval pipelines
- Tool-using AI agents
- Advanced multi-agent systems
- Real-time RAG workflows
- Production-oriented LLM applications
LEARNING FEATURES
- Bite-sized lessons that build from fundamentals to advanced topics
- Python examples with JavaScript support
- Quizzes, challenges, tips, and good-to-know explanations
- Hands-on project-based learning
- Progressive learning paths for beginners and experienced developers
- Cheat sheets for LangChain fundamentals, RAG, and agents
- Progress tracking to help you continue your learning journey
Start your LangChain Journey Today !
Whether you are beginning with LangChain or expanding your LLM engineering skills, Learn LangChain helps you study the concepts and patterns used to build real AI products.
WHAT YOU’LL LEARN
- LangChain fundamentals and setup
- LLMs, chat models, prompts, and structured output
- LCEL and composable application chains
- Memory, conversation workflows, and state
- Document loaders, text splitters, embeddings, and vector stores
- Retrieval-augmented generation, or RAG
- Advanced RAG patterns, including Graph RAG and Agentic RAG
- AI agents, tools, ReAct workflows, and multi-agent systems
- LangGraph concepts, nodes, state, and workflows
- LangSmith, LangServe, templates, observability, and debugging
- Vector databases, semantic search, and retrieval pipelines
- AI evaluation, testing, quality measurement, and RAG evaluation
- Streaming, caching, error handling, scaling, and production architecture
- LoRA and efficient LLM fine-tuning
- vLLM, model serving, inference, and deployment concepts
- CrewAI and modern multi-agent application patterns
- MCP concepts and connected AI workflows
BUILD HANDS-ON PROJECTS
Apply what you learn through practical projects, including:
- Q&A bots with RAG
- Multi-document research agents
- AI customer support systems
- Vector search and retrieval pipelines
- Tool-using AI agents
- Advanced multi-agent systems
- Real-time RAG workflows
- Production-oriented LLM applications
LEARNING FEATURES
- Bite-sized lessons that build from fundamentals to advanced topics
- Python examples with JavaScript support
- Quizzes, challenges, tips, and good-to-know explanations
- Hands-on project-based learning
- Progressive learning paths for beginners and experienced developers
- Cheat sheets for LangChain fundamentals, RAG, and agents
- Progress tracking to help you continue your learning journey
Start your LangChain Journey Today !
Latest updates
1.0