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Course Outline

Introduction

  • Evolution from algorithmic logic to automated workflows
  • Definition and application of no-code automation solutions for government operations
  • Survey of Make platform capabilities and integrated AI agents

Fundamentals of the Make Platform

  • Core components: scenarios, modules, and trigger events
  • Data mapping techniques across disparate applications
  • Implementation of filters and routing logic

Integrating Applications and Data Infrastructure

  • Utilization of webhooks and real-time triggers
  • Interaction with external APIs via HTTP modules
  • Management of centralized data stores

Development of Initial AI Agents

  • Integration of Large Language Models (LLMs) into automated scenarios
  • Optimization of prompts to ensure consistent and reliable outputs
  • Extraction and utilization of agent responses within workflows

Integrating Agents with Data Systems

  • Retrieval of enterprise data and execution of corresponding actions
  • Construction of multi-step decision chains
  • Implementation of human-in-the-loop verification checkpoints

End-to-End Automation Implementation

  • Execution of a comprehensive business process automation
  • Strategies for error handling and automated retry mechanisms
  • Best practices for monitoring and maintaining scenario integrity

Summary and Future Directions

  • Deliverable: deployment of an operational automated process enhanced by a connected AI agent for government use.

Requirements

Qualifications

  • Previous coding experience is not a prerequisite.
  • Familiarity with web-based applications and spreadsheet software.
  • A fundamental grasp of internal business operations.

Intended Audience

  • Administrative and operational personnel.
  • Supervisory staff and designated process owners.
  • Non-technical stakeholders seeking to implement AI-driven automation for government workflows.
 18 Hours

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