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Course Outline

Introduction to Agentic AI in Business Automation

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

Identifying Automation Opportunities

  • Analyzing existing workflows and associated pain points
  • Assessing the feasibility and ROI of AI-driven automation
  • Establishing success metrics and integration prerequisites

Designing Agentic Workflows

  • Architecting task-specific agents and orchestration-level systems
  • Crafting prompts and structuring logic for automation agents
  • Incorporating decision-making capabilities and exception handling

Integrating Agents with Business Systems

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

Applied Use Cases

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

Governance, Security, and Monitoring

  • Overseeing access control and data sensitivity
  • Configuring monitoring dashboards and alert systems
  • 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 understanding of business workflows and process automation
  • Familiarity with Python or API-based integration techniques
  • Practical experience utilizing productivity or automation tools

Audience

  • Product managers aiming to uncover automation opportunities
  • Automation engineers focused on deploying AI-driven workflows
  • Business analysts crafting data-informed business processes
 21 Hours

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