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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
Testimonials (1)
The trainer is patient and very helpful. He knows the topic well.