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Course Outline

Introduction to Agentic AI in Business Automation

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

Pinpointing Automation Opportunities

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

Architecting Agentic Workflows

  • Developing task-specific and orchestration-level agents
  • Structuring prompt design and logic for automation agents
  • Incorporating decision-making logic and exception handling

Connecting Agents to 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

Practical Use Cases

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

Governance, Security, and Monitoring

  • Controlling access and managing data sensitivity
  • Configuring monitoring dashboards and alert systems
  • Auditing and evaluating automated decisions

Practical Project: Constructing an Integrated AI Workflow

  • Selecting a target process for automation
  • Designing and deploying the AI agent
  • Conducting tests, evaluations, and optimizations

Wrap-up and Future Directions

Requirements

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

Target Audience

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

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