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Course Outline

Introduction to Agentic AI in Business Automation

  • Defining agentic AI and its significance for automation
  • Survey of tools and frameworks for developing intelligent agents
  • Enterprise applications: customer service, logistics, and marketing

Pinpointing Automation Opportunities

  • Assessing existing workflows and identifying pain points
  • Assessing feasibility and ROI for AI-driven automation
  • Establishing success metrics and integration prerequisites

Architecting Agentic Workflows

  • Creating task-specific and orchestration-level agents
  • Crafting prompts and structuring logic for automation agents
  • Incorporating decision-making processes and exception handling

Connecting Agents to Business Systems

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

Real-World Application Scenarios

  • Automating customer service and performing sentiment analysis
  • Forecasting supply chain demand and coordinating vendors
  • Optimizing marketing campaigns through AI-driven insights

Governance, Security, and Oversight

  • Controlling access and managing data sensitivity
  • Configuring monitoring dashboards and alert systems
  • Reviewing and auditing automated decisions

Practical Project: Constructing an Integrated AI Workflow

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

Conclusion and Future Directions

Requirements

  • Foundational knowledge of business workflows and process automation
  • Proficiency with Python or API-based integration systems
  • Practical experience utilizing productivity or automation software

Target Audience

  • Product managers looking to uncover automation potential
  • Automation engineers focused on deploying AI-driven workflows
  • Business analysts engaged in designing data-informed processes
 21 Hours

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