Designing Multi-Agent Workflows with AutoGen Studio Training Course

AutoGen is an open-source framework developed by Microsoft to facilitate the creation of multi-agent applications leveraging large language models, external tools, persistent memory, and user interaction.

This instructor-led, live training session, available via online or onsite delivery, is designed for senior developers and architects seeking to architect and deploy highly customized agents utilizing AutoGen’s Python APIs, function-calling features, and modular toolchains.

Upon completion of this training, participants will be capable of:

• Creating custom agents with role-specific logic and tool routing.
• Constructing dynamic workflows using advanced function calling and context switching.
• Integrating memory modules and planning frameworks within multi-agent teams.
• Managing multi-agent error states and implementing adaptive retry mechanisms.

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 program provides essential capabilities for government teams looking to enhance their autonomous system development for government missions.

AutoGen for Enterprise AI Automation provides practical instruction on deploying scalable, intelligent agent systems to streamline complex business operations via the AutoGen framework. This solution is designed specifically for government agencies seeking robust automation capabilities.

This instructor-led training, available online or onsite, targets intermediate to advanced AI professionals intent on implementing multi-agent architectures across enterprise platforms and processes using the AutoGen framework.

Upon completion of this training, participants will be equipped to:

• Architect and automate enterprise workflows utilizing AutoGen and large language model (LLM) agents.
• Integrate AutoGen with LangChain to enhance orchestration and context management.
• Develop Retrieval-Augmented Generation (RAG) pipelines and link enterprise data for contextual automation.
• Interface agents with enterprise platforms, including Slack, Jira, and SharePoint.
• Scale and monitor AutoGen deployments within production environments.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Course Customization Options

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

This program provides practical instruction on constructing Large Language Model (LLM) agent systems by leveraging Microsoft’s AutoGen framework. The curriculum is tailored for technical teams requiring robust solutions for government applications.

Delivered by expert instructors, this live training—available via online or onsite modalities—is intended for AI and automation specialists at an intermediate proficiency level. Participants will learn to design, deploy, and manage multi-agent architectures using Python and LLM technologies within federal workflows.

Upon completion of this course, attendees will demonstrate the ability to:

• Architect multi-agent systems utilizing the AutoGen framework.
• Define agent roles, functional capabilities, and coordination protocols.
• Implement function-calling mechanisms and memory management for inter-agent communication.
• Develop and validate Python-based LLM agent workflows suitable for operational deployment.

Instructional Methodology

• Facilitated lectures and technical discussions.
• Extensive practical exercises and skill-building activities.
• Direct implementation through a live laboratory environment.

Program Adaptability

• To arrange for government-specific customization of this curriculum, please contact the training coordination team.

This intensive one-day training program is specifically designed for government developers, data scientists, and artificial intelligence specialists to comprehend and leverage the capabilities of agentic AI systems through AutoGen v0.4.

Utilizing a combination of guided practical exercises and technical demonstrations, participants will acquire the skills necessary to construct, administer, and deploy multi-agent applications driven by Large Language Models (LLMs).

Upon completion, attendees will establish a robust understanding of AutoGen’s layered architecture, achieve proficiency in asynchronous inter-agent communication, and examine applicable use cases and governance best practices for developing scalable, intelligent applications for government missions.