Toruń

Sale szkoleniowe NobleProg, Bydgoska 1, Toruń, poland, 87-100

Sale szkoleniowe NobleProg w Toruniu znajdują się w biurze Coworking Toruń przy ulicy Bydgoskiej 1

Bydgoszcz

sale szkoleniowe NobleProg, ul. Dworcowa 94, Bydgoszcz, poland, 85-010

Sala szkoleniowa znajduje się przy ul. Dworcowej 94 w Bydgoszczy

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Building Dynamic Workflows with LangGraph and LLM Agents

 14 godzin

LangGraph is a framework for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

By the end of this training, participants will be able to:

  • Design graph-based workflows that coordinate LLM agents, tools, and memory.
  • Implement conditional routing, retries, and fallbacks for robust execution.
  • Integrate retrieval, APIs, and structured outputs into agent loops.
  • Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

  • Interactive lecture and facilitated discussion.
  • Guided labs and code walkthroughs in a sandbox environment.
  • Scenario-based design exercises and peer reviews.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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LangGraph Foundations: Graph-Based LLM Prompting and Chaining

 14 godzin

LangGraph is a framework for building graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at beginner-level developers, prompt engineers, and data practitioners who wish to design and build reliable, multi-step LLM workflows using LangGraph.

By the end of this training, participants will be able to:

  • Explain core LangGraph concepts (nodes, edges, state) and when to use them.
  • Build prompt chains that branch, call tools, and maintain memory.
  • Integrate retrieval and external APIs into graph workflows.
  • Test, debug, and evaluate LangGraph apps for reliability and safety.

Format of the Course

  • Interactive lecture and facilitated discussion.
  • Guided labs and code walkthroughs in a sandbox environment.
  • Scenario-based exercises on design, testing, and evaluation.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
Więcej...

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LangGraph Konsultacje
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