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🚀 Comprehensive Developer Certification

Build Enterprise AI Applications
with the Lang Ecosystem

A hands-on course covering LangChain, LangGraph, LangSmith, Langfuse, and LangServe — from RAG pipelines to production-grade multi-agent systems with full observability.

📚 17 Modules ⏱ ~60 Hours 💻 100+ Code Examples 🎯 80% Pass Threshold 🏆 Completion Certificate
Start Course → Browse Modules
17
Modules
~60
Hours of Content
0
Completed by You
80%
To Pass Each Quiz
5
Core Frameworks
What You'll Learn

From First Chain to Production Agent

This course takes you from LangChain fundamentals through advanced multi-agent orchestration, full observability, guardrails, multimodal AI, and enterprise deployment — with every concept backed by working code.

🔗
LangChain & LCEL
Chains, prompts, memory, tools and the Expression Language that ties it all together.
🗂️
RAG Pipelines
Hybrid retrieval, re-ranking, parent-document retrievers, and RAGAS evaluation.
🕸️
LangGraph Agents
Stateful graphs, checkpointing, human-in-the-loop, and multi-agent coordination.
🧩
Orchestration Patterns
Supervisor, plan-and-execute, reflection, map-reduce, debate, and swarm patterns.
🛡️
Guardrails & Safety
Input/output validation, PII detection, NeMo Guardrails, and Guardrails AI.
🔭
Full Observability
LangSmith tracing & eval plus Langfuse open-source monitoring for every call.
🌊
Streaming
Token-level SSE and WebSocket streaming from LangGraph to browser UIs.
🖼️
Multimodal AI
Vision, audio transcription, document intelligence, and multimodal RAG.
Tech Stack

Frameworks & Tools Covered

🦜 LangChain 0.3 🕸️ LangGraph 0.2 🔬 LangSmith 📊 Langfuse 🚀 LangServe 🐍 Python 3.11+ ⚡ FastAPI 🎈 Streamlit ⛓️ Chainlit ▲ Next.js 🛡️ Guardrails AI 🔒 NeMo Guardrails 🔍 Presidio (PII) 📦 ChromaDB / pgvector 🔄 Redis 🐳 Docker
Prerequisites

What You Should Know Before Starting

✓
Python 3.10+Functions, classes, async/await, virtual environments.
✓
REST APIsHTTP methods, JSON, status codes, making API calls.
✓
LLM ConceptsWhat a language model is; tokens, temperature, prompts.
✓
Git BasicsClone, commit, and environment variable management.
✓
Command LineRunning Python scripts and pip install commands.
ℹ
TypeScript (optional)Helpful for UI modules but not required.
Course Modules

17 Modules — Sequential Unlocking

Each module builds on the last. Score 80%+ on the knowledge check to unlock the next module.

MODULE 00
Course Introduction & Environment Setup
Ecosystem map, toolchain installation, API key management, and your first LLM call.
⏱ 1 hr❓ 5 questions
▶ Start
MODULE 01
LangChain Foundations
LCEL pipe syntax, ChatModels, PromptTemplates, chains, memory, and tool calling.
⏱ 3 hrs❓ 10 questions
🔒 Locked
MODULE 02
RAG: Retrieval Augmented Generation
Document loaders, chunking, vector stores, hybrid search, re-ranking, and RAGAS evaluation.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 03
LangGraph: Stateful Agentic Workflows
StateGraph, nodes, edges, checkpointing, and human-in-the-loop patterns.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 04
Agent Orchestration Patterns
ReAct, plan-and-execute, reflection, supervisor, map-reduce, debate, and swarm patterns.
⏱ 5 hrs❓ 15 questions
🔒 Locked
MODULE 05
Agent-to-Agent Handover
Command-based handover, swarm routing, context preservation, and cross-service handoff.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 06
Resiliency & Fault Tolerance
Retry strategies, fallback chains, circuit breakers, timeouts, idempotency, and chaos testing.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 07
Debugging & Troubleshooting Agents
LangGraph Studio, LangSmith traces, state inspection, structured logging, and eval-driven debugging.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 08
LangSmith: Observability & Evaluation
Tracing, LLM-as-judge evaluation, datasets, prompt hub, and CI/CD integration.
⏱ 3 hrs❓ 10 questions
🔒 Locked
MODULE 09
Langfuse: Open-Source Observability
Self-hosted tracing, scoring pipelines, prompt versioning, and cost attribution dashboards.
⏱ 3 hrs❓ 10 questions
🔒 Locked
MODULE 10
Guardrails & Safety
PII detection, prompt injection blocking, NeMo Guardrails, Guardrails AI, and LangGraph guardrail nodes.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 11
Multimodal Interaction
Vision models, audio transcription, document intelligence, multimodal RAG, and image-generating tools.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 12
Streaming Interactions with LLMs
LangChain .astream(), LangGraph streaming modes, SSE with FastAPI, WebSockets, and frontend rendering.
⏱ 4 hrs❓ 10 questions
🔒 Locked
MODULE 13
Enterprise Patterns & Production Readiness
Multi-tenancy, semantic caching, JWT auth, Prometheus metrics, and horizontal scaling.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 14
LangServe: Deploying Chains & Agents as APIs
add_routes(), five auto-generated endpoints, RemoteRunnable, auth middleware, and Docker deployment.
⏱ 4 hrs❓ 12 questions
🔒 Locked
MODULE 15
UI Frameworks for Enterprise AI Apps
Streamlit, Chainlit, Gradio, Next.js + Vercel AI SDK, React hooks, Open WebUI, and HTMX.
⏱ 5 hrs❓ 12 questions
🔒 Locked
MODULE 16
Capstone Project
Build a complete enterprise knowledge assistant combining every concept from the course.
⏱ 8 hrs❓ 25 questions
🔒 Locked
How It Works

Sequential Unlock System

  1. Read the module content
    Each module contains conceptual explanations, architecture diagrams, annotated code examples, and common pitfall callouts.
  2. Run the code examples
    Copy any snippet using the ⎘ Copy button, paste it into your environment, and experiment with modifications.
  3. Pass the knowledge check
    Score 80% or higher on the multiple-choice quiz at the end of each module. You can retry as many times as you need.
  4. Unlock the next module
    Passing the quiz immediately unlocks the next module and records your progress in the browser.
  5. Complete the Capstone
    Build a full enterprise AI application in Module 16 and earn your completion certificate.