LangGraph Mastery: Develop LLM Agents with LangGraph

Andrei Dumitrescu develops agent applications from graph components into reflection and retrieval-based research workflows. LangSmith tracing provides a way to inspect behavior during development. It suits learners already proficient in Python and LangChain who want to understand how an application’s state, tools and model calls participate in a larger controlled process.

What you will learn

• Explore ReAct and reflection patterns.
• Trace agent behavior with LangSmith.
• Connect retrieval knowledge bases with research workflows.

Who this suits

Good Python and LangChain knowledge is required, including types, classes, environment variables, prompts and output parsers.

Before you enroll

Model APIs, search tools and hosting may cost extra. Check framework and model versions before reproducing recorded code. Use fictional data and restrict tool permissions while learning. Inspect state transitions, failures and retry behavior rather than judge an agent from one successful answer. Generated output and autonomous actions need validation; a project demonstration does not establish production reliability.

Udemy offers paid purchase or subscription access depending on the current course and region. Paid teaching courses provide completion certificates under Udemy’s policy. Check current access terms and any separate software or material costs before enrolling.

Put it into practice

Trace a fictional research-agent run and identify which retrieved source supports each generated claim, including a case where the source is insufficient.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

Where a formal level is unavailable, the level filter is an editorial estimate based on the published audience and requirements. Duration filters reflect the listed video time; exercises and independent practice can take longer.

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Supporting provider sources

• support.udemy.com: supporting course information