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 Duration 21 hours

Course Outline

Core Principles of Agentic AI Systems

  • Defining autonomous agents: operational definitions and classification frameworks
  • The agent execution cycle: sensing, deliberation, execution, and feedback loops
  • Establishing boundaries for agent responsibilities and operational scope

Python Development Ecosystems and Agent Frameworks

  • Leveraging LangChain and equivalent SDKs to initialize agent architectures
  • Implementing asynchronous processing, task queuing, and subprocess control
  • Managing software packaging, virtual environments, and consistent development standards

Integration of External Tools and Services

  • Architecting secure tool interfaces and safe invocation methodologies
  • Linking to web services, data repositories, and internal government systems
  • Enforcing credential management, secret protection, and least-privilege access models

State, Memory, and Contextual Governance

  • Optimizing short-term context windows and prompt construction techniques
  • Designing persistent memory structures: Redis, vector databases, and retrieval strategies
  • Maintaining data consistency, caching efficiency, and memory integrity

Workflow Orchestration, Planning, and Multi-Step Execution

  • Sequencing actions, coordinating sub-agents, and decomposing complex tasks
  • Evaluating algorithmic planning versus heuristic-based orchestration methods
  • Mitigating failures, implementing retry logic, and executing compensating transactions

Security Assurance, Testing, and Observability

  • Developing threat models, conducting red-team exercises, and sanitizing inputs and outputs
  • Executing unit, integration, and end-to-end validation for agent systems
  • Establishing logging, metrics collection, tracing, and alerting for behavioral oversight

Deployment Strategies, Scalability, and Agent MLOps

  • Implementing containerization, continuous integration/deployment pipelines, and release controls
  • Optimizing cost structures, applying rate limits, and maximizing resource efficiency
  • Establishing monitoring protocols, governance frameworks, and operational response plans

Summary and Strategic Next Steps

Requirements

  • Proficiency in Python programming
  • Experience with REST APIs and asynchronous input/output handling
  • Knowledge of machine learning concepts and pretrained large language models

Target Audience

  • Machine learning engineers
  • AI developers
  • Software engineers

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