Python for Autonomous Agents: Tooling, SDKs & Orchestration Training Course

Foundations of Python Environments for Agentic Development

• Installing Python, setting up virtual environments, and managing dependencies
• Leveraging Git and Docker for version control and environment isolation
• Adopting best practices for creating reproducible environments

Introduction to Agent SDKs and Frameworks

• Exploring LangChain, AutoGen, and other emerging SDKs
• Understanding agent structure and lifecycle: perception, reasoning, and action
• Evaluating SDK capabilities and architectural approaches

Developing Operational Agents in Python

• Building a basic agent using LangChain
• Linking agents to external tools and APIs
• Managing input/output, memory, and data persistence

Integrating Tools and APIs

• Defining and registering tools for agent utilization
• Implementing secure API integration and key management
• Utilizing external data sources and custom function calls

Orchestrating Agents and Communication Patterns

• Facilitating multi-agent collaboration using AutoGen
• Managing task delegation and planning logic
• Implementing event-driven and asynchronous orchestration

Testing, Debugging, and Observability

• Testing agents with mock inputs in controlled environments
• Debugging message flows and tool invocations
• Incorporating structured logging and performance metrics

Deployment and Production-Readiness

• Packaging and containerizing Python agent services
• Integrating with CI/CD pipelines
• Scaling, monitoring, and maintaining long-running agents

Conclusion and Future Directions