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Course Outline

Foundations of Agentic AI in Business Automation

  • Understanding agentic AI and its strategic value in automation
  • Surveying tools and frameworks for creating intelligent agents
  • Enterprise applications: customer support, logistics, and marketing

Locating Automation Opportunities

  • Analyzing current workflows and identifying bottlenecks
  • Assessing feasibility and return on investment for AI automation
  • Setting success metrics and defining integration needs

Architecting Agentic Workflows

  • Building task-specific agents and orchestration-level systems
  • Structuring prompts and logic for effective automation agents
  • Incorporating decision-making logic and exception management

Connecting Agents to Business Systems

  • Linking AI agents to CRMs, ERPs, and communication platforms
  • Leveraging Zapier, Make, or Power Automate for orchestration
  • Developing API-based integrations using Python

Practical Use Cases

  • Automating customer service and analyzing sentiment
  • Forecasting supply chain demand and coordinating vendors
  • Optimizing marketing campaigns with AI-generated insights

Governance, Security, and Oversight

  • Controlling access and managing data sensitivity
  • Configuring monitoring dashboards and alert systems
  • Reviewing and auditing automated decision-making processes

Capstone Project: Constructing an Integrated AI Workflow

  • Selecting a target process for automation
  • Designing and deploying the AI agent
  • Testing, assessing performance, and refining the solution

Conclusion and Future Pathways

Requirements

  • Fundamental grasp of business workflows and process automation
  • Proficiency with Python or API-based integration concepts
  • Practical experience with productivity or automation software

Intended Audience

  • Product managers looking to uncover automation potential
  • Automation engineers responsible for deploying AI-driven workflows
  • Business analysts crafting data-informed business processes
 21 Hours

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