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Course Outline
Introduction to Quark
- Overview of Quark as an AI agent platform
- Understanding the architecture and key components
- Setting up Quark for development
Building Intelligent Agents with Quark
- Agent design and decision-making frameworks
- Developing automation workflows with Quark
- Implementing decision trees and state machines
Integrating Quark with Data and Systems
- Data ingestion and processing with Quark
- Integrating Quark with external APIs and databases
- Optimizing real-time decision-making
Advanced Automation with Quark
- Event-driven automation with Quark
- Creating dynamic workflows and decision matrices
- Handling complex decision logic
Testing and Monitoring Intelligent Agents
- Implementing testing frameworks for Quark agents
- Monitoring agent performance and efficiency
- Troubleshooting and debugging common issues
Case Studies and Real-World Applications
- Exploring successful use cases of Quark for automation
- Applying Quark to streamline business processes
- Building a prototype intelligent agent
Summary and Next Steps
Requirements
- Basic programming skills in Python
- Familiarity with AI and automation concepts
Audience
- AI engineers
- Software developers
14 Hours
