LangGraph & LLM Agents Workflows Training in Ontario

LangGraph & LLM Agents Workflows Training in Ontario, Canada

This course introduces participants to LangGraph, a framework for building graph-based Large Language Model (LLM) applications and agent workflows

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LangGraph & LLM Agents Workflows Training is a professional training program delivered by ProgNXT in Ontario, Canada. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this LangGraph & LLM Agents Workflows Training course with hands-on, instructor-led sessions. This course introduces participants to LangGraph, a framework for building graph-based Large Language Model (LLM) applications and agent workflows....

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: SAR56
21 Hrs
Last Updated: April 2026

Course Rating5/5

This course introduces participants to LangGraph, a framework for building graph-based Large Language Model (LLM) applications and agent workflows. It covers the fundamentals of LLM orchestration, agent design, state management, and workflow automation. By the end, learners will be able to design, implement, and deploy robust LLM-driven applications with multi-step reasoning, memory, and tool integrations.

Welcome to the official LangGraph & LLM Agents Workflows Training certification program in Ontario, Canada. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic knowledge of Python programming
Understanding of LLMs and NLP concepts
Familiarity with LangChain basics (preferred, not mandatory)
Awareness of APIs and integration with external tools

By completing this course, participants will:

Understand LangGraph architecture and its role in LLM orchestration.
Build agent workflows with stateful reasoning.
Implement multi-agent collaboration for complex tasks.
Integrate tools, APIs, and memory into LLM workflows.
Design scalable graph-based applications.
Apply best practices for reliability, evaluation, and optimization of LLM agents.

Proficiency in LangGraph framework
Designing graph-based agent workflows
Building stateful and collaborative LLM agents
Tool and API integration with LLMs
Debugging, evaluating, and optimizing LLM pipelines
Applying LLMOps practices for real-world deployment

LangGraph concepts and architecture
Building stateful agent workflows
Multi-agent collaboration and communication
Workflow evaluation, debugging, and optimization

Participants who attend all sessions and successfully complete the course assessments will receive a ProgNXT Certificate of Completion.

Introduction to LangGraph & Agent Workflows

Evolution of LLM Orchestration: From LangChain to LangGraph
Introduction to LangGraph
- Graph-based workflow design
- Key concepts: nodes, edges, state, persistence
LLM Agents Fundamentals
- Single-agent workflows
- Prompt-driven task orchestration

Advanced Agent Design & Multi-Agent Workflows

Stateful Agents with LangGraph
- Managing memory and context across workflows
- Error handling and recovery
Multi-Agent Collaboration
- Agent communication patterns
- Task delegation and orchestration
Tool Integration
- Connecting APIs, databases, and external tools
- Using retrievers and vector databases

Scaling, Evaluation & Best Practices

Workflow Optimization and Performance
- Parallelism and concurrency in LangGraph
- Handling long-running tasks
Evaluation and Debugging
- Tracing, logging, and error analysis
- LLM evaluation metrics and testing
Production Deployment & LLMOps
- Scaling LangGraph workflows
- Security, governance, and reliability

Hands-on Exercises

Summary and Conclusion

Instructor presentations and reference notes
Sample code templates and workflow blueprints
Lab exercises

Quizzes
Hands-on labs and workflow implementations

ProgNXT Certificate of Completion will be awarded to participants who successfully complete the course and assessments.

LangGraph & LLM Agents Workflows Training Events in ontario

Online Events

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More Upcoming Session Dates

October 2026

📍 Ontario, Canada

21st Oct 2026→23rd Oct 2026

🌐 Online Instructor-Led

26th Oct 2026→28th Oct 2026

November 2026

🌐 Online Instructor-Led

1st Nov 2026→3rd Nov 2026

📍 Ontario, Canada

12th Nov 2026→14th Nov 2026

📍 Ontario, Canada

22nd Nov 2026→24th Nov 2026

🌐 Online Instructor-Led

27th Nov 2026→29th Nov 2026

December 2026

📍 Ontario, Canada

9th Dec 2026→11th Dec 2026

🌐 Online Instructor-Led

10th Dec 2026→12th Dec 2026

📍 Ontario, Canada

23rd Dec 2026→25th Dec 2026

🌐 Online Instructor-Led

28th Dec 2026→30th Dec 2026

Events for other courses in Ontario, Canada

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LangGraph & LLM Agents Workflows Training in Ontario