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Duration 21 hours
Course Outline
Foundations of Python Environments for Agentic Development
- Establishing Python, virtual environments, and managing dependencies
- Leveraging Git and Docker for version control and isolation
- Best practices for ensuring reproducible environments
Exploring Agent SDKs and Frameworks
- LangChain, AutoGen, and other emerging SDKs
- Agent architecture and lifecycle: perception, reasoning, and execution
- Evaluating SDK features and architectural approaches
Developing Functional Agents in Python
- Constructing 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 interaction
- Secure API integration and key administration
- Utilizing external data sources and custom function invocations
Orchestrating Agents and Communication Patterns
- Facilitating multi-agent collaboration via AutoGen
- Delegating tasks and structuring planning logic
- Implementing event-driven and asynchronous orchestration
Testing, Debugging, and Observability
- Testing agents using mock inputs and controlled settings
- Debugging message flows and tool executions
- Implementing structured logging and tracking performance metrics
Deployment and Production Readiness
- Packaging and containerizing Python agent services
- Integrating with CI/CD pipelines
- Scaling, monitoring, and sustaining long-running agents
Wrap-up and Future Directions
Requirements
- Solid grasp of Python programming and package dependency management
- Hands-on experience with REST APIs and JSON data structures
- Foundational knowledge of asynchronous I/O operations in Python
Target Audience
- Backend engineers
- Platform engineers
- ML engineers
