AutoGen is an open-source framework for building LLM agents that think together—collaborating through dialogue to solve complex tasks autonomously.
Our instructor-led courses teach how to orchestrate multiple agents, customize behaviors with Python, and deploy multi-role AI systems for research, automation, and rapid prototyping.
Training is available as online live sessions via interactive remote desktop, or as onsite live training in Zakopane, featuring hands-on labs in prompt engineering, agent workflows, and tool integration.
Whether you're building your first agent team or scaling complex AI pipelines, onsite courses can be held at your location in Zakopane or at a NobleProg corporate training center for immersive, team-based learning.
Also known as AutoGen Studio or Multi-Agent LLM Framework, this training is ideal for developers, researchers, and innovators exploring the next frontier of generative AI.
NobleProg – Your Local Training Provider
Zakopane
Dafne, Jagiellońska 30, Zakopane, Poland, 34-500
The training room is located just 350 meters from the railway and bus stations and 700 meters from Krupówki, the main shopping street in Zakopane. There is a fenced parking area on the premises, providing convenience for participants traveling by car and facilitating access to the facility.
AutoGen for Enterprise AI Automation is a hands-on course focused on implementing scalable, intelligent agent systems to automate complex business operations using the AutoGen framework.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level AI professionals who wish to deploy multi-agent architectures across enterprise platforms and processes using the AutoGen framework.
By the end of this training, participants will be able to:
Design and automate enterprise workflows using AutoGen and LLM agents.
Integrate AutoGen with LangChain for advanced orchestration and context handling.
Build RAG pipelines and connect enterprise data for contextual automation.
Connect agents with enterprise platforms like Slack, Jira, and SharePoint.
Scale and monitor AutoGen deployments in production environments.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Building LLM Agent Systems with AutoGen is a hands-on course focused on developing multi-agent systems using Microsoft’s AutoGen framework for large language models (LLMs).
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI and automation professionals who wish to design, implement, and orchestrate multi-agent systems using AutoGen with Python and LLMs.
By the end of this training, participants will be able to:
Design multi-agent architectures using the AutoGen framework.
Configure agent roles, capabilities, and coordination behaviors.
Use function-calling and memory handling for agent interactions.
Build and test Python-based LLM agent workflows for real use cases.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This 1-day workshop, designed for developers, data scientists, and AI enthusiasts, will help you understand and harness the power of agentic AI systems using AutoGen v0.4.
Through a mix of hands-on exercises and practical demonstrations, you’ll learn how to build, manage, and deploy multi-agent applications powered by Large Language Models (LLMs).
By the end of the course, you'll gain a solid foundation in AutoGen’s layered architecture, master asynchronous communication between agents, and explore real-world use cases and best practices for developing scalable and intelligent LLM-driven applications.
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Testimonials (1)
Trainer responding to questions on the fly.
Adrian
Course - Agentic AI Unleashed: Crafting LLM Applications with AutoGen
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