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Course Outline

Introduction to Agentic AI in Business Automation

  • Defining agentic AI and its significance for automation
  • Surveying the tools and frameworks used to build intelligent agents
  • Enterprise applications: customer service, logistics, and marketing

Identifying Automation Opportunities

  • Mapping existing workflows and identifying pain points
  • Assessing the feasibility and ROI of AI-driven automation
  • Setting success metrics and defining integration requirements

Designing Agentic Workflows

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

Integrating Agents with 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

Applied Use Cases

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

Governance, Security, and Monitoring

  • Overseeing access control and data sensitivity
  • Configuring monitoring dashboards and alerts
  • Reviewing and auditing automated decisions

Hands-on Project: Building an Integrated AI Workflow

  • Selecting a target process for automation
  • Designing and deploying the AI agent
  • Conducting testing, evaluation, and optimization

Summary and Next Steps

Requirements

  • A foundational grasp of business workflows and process automation
  • Proficiency with Python or API-based integrations
  • Practical experience with productivity or automation tools

Target Audience

  • Product managers looking to uncover automation opportunities
  • Automation engineers tasked with building AI-driven workflows
  • Business analysts focused on designing data-informed processes
 21 Hours

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