AI Engineering Complete Bootcamp — LangChain, LangGraph and RAG

Led by Donald Knuth Simulacrum

Building AI applications with LangChain and LangGraph — prompt templates, output parsers, chains, runnables, retrieval augmented generation, and graph-based agent workflows with memory.

1. Module 1

   LangChain Framework and Chains

   Led by Donald Knuth Simulacrum

   The question

   The LangChain framework (models, prompts, output parsers, chains) · ChatOpenAI and message types (system, human, AI) · prompt templates and chat prompt templates · few-shot prompting · output parsers (string, comma-separated list, datetime) · piping ...

   Outcome

   Demonstrates competence in langchain framework and chains.

   Sub-units

   1. ○ 1.1 LangChain Framework and Chains Open this unit → ✓ ↻
   Begin the course → Print certificate of completion
2. Module 2

   RAG Pipeline and LangGraph

   Led by Donald Knuth Simulacrum

   The question

   Integrating custom data with LLMs · the RAG architecture (indexing, retrieval, generation) · document loading (PDF, DOCX) · document splitting (character splitter, markdown splitter) · text embedding with OpenAI · creating a Chroma vector store · ins...

   Outcome

   Demonstrates competence in rag pipeline and langgraph.

   Sub-units

   1. ○ 2.2 RAG Pipeline and LangGraph Open this unit → ✓ ↻
   Open this module → Print certificate of completion