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Course Outline

Overview of Generative AI and Autonomous Systems

  • Definitions of generative artificial intelligence and autonomous agents
  • Distinctions and synergies between the two technologies
  • Industry applications and emerging market trends

Generative AI Infrastructure and Utility Frameworks

  • Core transformer architectures, including GPT, LLaMA, and Claude models
  • Differentiating fine-tuning methodologies from in-context learning approaches
  • Accessible platforms: ChatGPT, Hugging Face Transformers, and Google AI Studio for government

Prompt Engineering for Operational Control and Standardization

  • Structured prompt patterns for document drafting, code generation, and information synthesis
  • Techniques including few-shot, zero-shot, and chain-of-thought reasoning
  • Utilization of established prompt libraries and validation tools

Frameworks for Autonomous Agents

  • Conceptual definition and historical development of agentic AI systems
  • System architecture components: planning mechanisms, memory storage, tool integration, and self-evaluation
  • Leading open-source frameworks: AutoGPT, BabyAGI, CrewAI, and LangGraph

Architecture and Deployment of Autonomous Agents

  • Strategic objective setting and hierarchical task decomposition
  • Integration of external APIs for search capabilities, data retention, and computational functions
  • Multi-agent interoperability and human-in-the-loop oversight protocols for government operations

Strategic Applications and Deployment Scenarios

  • Comparative analysis of content generation versus task orchestration workflows
  • Applications in enterprise efficiency, public sector customer service, and structured data extraction
  • Principles for secure, ethical, and accountable implementation

Executive Summary and Forward Planning

Requirements

  • Proficiency in artificial intelligence and machine learning principles
  • Demonstrated expertise with application programming interfaces (APIs) or scripting languages, including Python
  • Knowledge of prompt engineering techniques and large language model implementation for government applications

Target Audience

  • Artificial intelligence developers and engineers
  • Innovation and research and development (R&D) units
  • Technical product managers evaluating agentic AI solutions
 14 Hours

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