Python for Autonomous Agents: Tooling, SDKs & Orchestration Training Course
Python serves as the foundational language driving the development and coordination of autonomous AI agents. This course emphasizes practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to construct, connect, and manage agent workflows.
This instructor-led, live training (online or onsite) is designed for intermediate-level backend engineers, platform engineers, and ML engineers who aim to implement and coordinate autonomous agents using Python tooling and APIs.
By the end of this training, participants will be able to:
- Set up and configure Python-based environments for agentic systems.
- Utilize popular agent SDKs like LangChain and AutoGen to develop functional agents.
- Integrate tools and APIs to enhance agent capabilities.
- Orchestrate multi-agent workflows and communication patterns.
- Apply best practices for debugging, testing, and maintaining agentic codebases.
**Format of the Course**
- Interactive lecture and discussion.
- Hands-on programming exercises and live demonstrations.
- Practical projects building end-to-end agent workflows.
**Course Customization Options**
- To request a customized training for government or other specific needs, please contact us to arrange.This course is available as onsite live training in US Government or online live training.
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Course Outline
Introduction to Python Environments for Agentic Development for Government
- Setting up Python, virtual environments, and dependency management for government projects
- Using Git and Docker for versioning and isolation in government applications
- Best practices for creating reproducible environments for government use
Overview of Agent SDKs and Frameworks for Government
- Evaluation of LangChain, AutoGen, and other emerging SDKs for government purposes
- Agent structure and lifecycle: perception, reasoning, and action in a governmental context
- Comparing SDK capabilities and architecture styles suitable for government operations
Building Functional Agents in Python for Government
- Creating a simple agent with LangChain tailored for government needs
- Connecting agents to external tools and APIs used by government agencies
- Handling input/output, memory, and persistence in government systems
Tool and API Integration for Government
- Defining and registering tools for agent use in government applications
- Secure API integration and key management for government data
- Using external data sources and custom function calls for government tasks
Agent Orchestration and Communication Patterns for Government
- Multi-agent collaboration using AutoGen in government projects
- Task delegation and planning logic for efficient government operations
- Event-driven and asynchronous orchestration for government workflows
Testing, Debugging, and Observability for Government Agents
- Testing agents with mock inputs and controlled environments to ensure reliability in government systems
- Debugging message flow and tool invocation for smooth operation in government applications
- Implementing structured logging and performance metrics for enhanced observability in government agents
Deployment and Production Considerations for Government Agents
- Packaging and containerizing Python agent services for government deployment
- Integrating with CI/CD pipelines to streamline development for government projects
- Scaling, monitoring, and maintaining long-running agents in government environments
Summary and Next Steps for Government
Requirements
- An understanding of Python programming and package management for government applications
- Experience with REST APIs and JSON data structures in a public sector context
- Basic familiarity with asynchronous I/O in Python, suitable for government projects
Audience
- Backend engineers working in the public sector
- Platform engineers supporting governmental systems
- Machine learning engineers focused on government initiatives
21 Hours
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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