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Duration 21 hours
Course Outline
Foundations of Python Environments for Agentic Development
- Configuring Python, virtual environments, and dependency management.
- Leveraging Git and Docker for version control and isolation.
- Establishing best practices for reproducible development environments.
Introduction to Agent SDKs and Frameworks
- Exploring LangChain, AutoGen, and other emerging SDKs.
- Understanding agent structure and lifecycle: perception, reasoning, and action.
- Comparing SDK capabilities and architectural approaches.
Developing Functional 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.
- Ensuring secure API integration and key management.
- Incorporating external data sources and custom function calls.
Orchestrating Agents and Communication Patterns
- Facilitating multi-agent collaboration with AutoGen.
- Implementing task delegation and planning logic.
- Designing event-driven and asynchronous orchestration strategies.
Testing, Debugging, and Observability
- Testing agents using mock inputs and controlled settings.
- Debugging message flows and tool invocations.
- Implementing structured logging and performance metrics.
Deployment and Production Readiness
- Packaging and containerizing Python-based agent services.
- Integrating with CI/CD pipelines.
- Scaling, monitoring, and maintaining long-running agents.
Recap and Future Directions
Requirements
- Solid grasp of Python programming and package management.
- Hands-on experience with REST APIs and JSON data structures.
- Fundamental knowledge of asynchronous I/O in Python.
Target Audience
- Backend engineers.
- Platform engineers.
- ML engineers.
