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Course Outline

Introduction to Agentic AI in Business Automation

  • Understanding agentic AI and its significance in automation
  • Overview of essential tools and frameworks for building intelligent agents
  • Enterprise applications: customer service, logistics, and marketing

Identifying Automation Opportunities

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

Designing Agentic Workflows

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

Integrating Agents with Business Systems

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

Applied Use Cases

  • Automating customer service and conducting sentiment analysis
  • Predicting supply chain demand and coordinating with vendors
  • Optimizing marketing campaigns through 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

Conclusion and Future Steps

Requirements

  • Fundamental knowledge of business workflows and process automation
  • Working familiarity with Python or API-based integrations
  • Practical experience with productivity or automation software

Target Audience

  • Product managers looking to uncover automation opportunities
  • Automation engineers focused on deploying AI-driven workflows
  • Business analysts designing data-centric business processes
 21 Hours

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