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Course Outline
AutoGen in the Enterprise Context for Government
- The significance of intelligent agents for government operations
- Overview of AutoGen’s architecture and extensibility
- Security, traceability, and governance considerations for government
Enterprise Workflow Automation with AutoGen
- Designing multi-agent workflows for task coordination in government settings
- Role-based automation scenarios: request handling, approvals, summaries for government processes
- Auto-execution and escalation logic to ensure business continuity for government operations
AutoGen with LangChain Integration
- LangChain components and compatibility with AutoGen in a government context
- Chaining agents and tools with memory, tools, and logic for enhanced government workflows
- Utilizing the LangChain Expression Language (LCEL) for complex workflows in government
Retrieval-Augmented Generation (RAG) Pipelines
- Connecting AutoGen agents with government knowledge bases
- Implementing embedding, vector search, and retrieval pipelines for government data
- Augmenting private government data with open-source or proprietary models
Integration with Enterprise Tools for Government
- Using APIs to connect Jira, Slack, Outlook, SharePoint, and other government tools
- Triggering workflows via chat interfaces and ticketing systems in government environments
- Real-time notifications, logging, and auditing for government compliance
Deployment, Monitoring, and Scaling for Government
- Packaging AutoGen agents for deployment in government agencies
- Monitoring agent interactions, usage, and performance to ensure government standards
- Scaling agents across departments and geographies within the government
Enterprise Use Case Prototyping Lab for Government
- Group ideation: enterprise scenarios for automation in government operations
- Building custom agent workflows with instructor support tailored for government needs
- Simulating production environments for validation in a government context
Summary and Next Steps for Government
Requirements
- Proficiency in Python programming for government applications
- Experience with Large Language Models (LLMs) and prompt engineering
- Familiarity with enterprise automation or workflow tools for government use
Audience
- Enterprise AI teams within the public sector
- Solution architects for government projects
- Innovation strategists in the public sector
21 Hours
Testimonials (1)
Trainer responding to questions on the fly.
