Build Real AI Agents with LangGraph and ADK
Nine practical modules on LLMs, RAG, LangGraph, Google ADK, agent architectures and deployment.
What's inside
9 modules,
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Introduces LLMs, prompting, and LangChain for building your first application chains.
Builds summarization and orchestration workflows with LangChain and LangGraph.
Designs RAG systems that retrieve relevant sources to answer user questions.
Explores advanced RAG strategies to improve retrieval, context, and answer quality.
Compares agent architectures and implements agents with LangGraph.
Develops agents with Google ADK, from core components to tool interactions.
Applies exercises from Building LLM Applications to practical agent use cases.
Examines architectural patterns for structuring agents and their tools.
Connects agents with A2A and prepares agent systems for deployment.