Course Outline

Introduction to Generative AI and Agentic AI for Government

  • Definitions: What is Generative AI? What is Agentic AI?
  • Distinguishing characteristics and complementary roles of generative and agentic AI
  • Application examples and emerging trends across various sectors, including public service

Generative AI Architecture and Tools for Government

  • Transformer models: GPT, LLaMA, Claude, and others
  • Differentiating between fine-tuning and in-context learning
  • Utilizing tools such as ChatGPT, Hugging Face Transformers, and Google AI Studio for government applications

Prompt Engineering for Control and Structure in Government

  • Effective prompt patterns for writing, coding, summarization, and more
  • Techniques including few-shot, zero-shot, and chain-of-thought prompting
  • Leveraging prompt libraries and testing tools to enhance government workflows

Understanding Agentic AI for Government

  • Definition and evolution of agentic AI in the context of public sector applications
  • Architectural components: planning, memory, tools, and self-reflection
  • Popular frameworks: AutoGPT, BabyAGI, CrewAI, LangGraph for government use

Designing and Deploying Autonomous Agents for Government

  • Setting goals and decomposing tasks for effective agent deployment
  • Integrating tools and APIs (search, memory, code) into government systems
  • Coordinating multi-agent operations and ensuring human-in-the-loop oversight for accountability

Use Cases and Implementation Scenarios for Government

  • Comparing content generation with task orchestration in government settings
  • Enhancing enterprise productivity, customer support, and data extraction within public sector organizations
  • Ensuring responsible and secure implementation of AI technologies for government operations

Summary and Next Steps for Government

Requirements

  • A comprehensive understanding of artificial intelligence and machine learning principles
  • Practical experience working with application programming interfaces (APIs) or scripting languages such as Python
  • Knowledge of prompt engineering or the utilization of large language models

Audience

  • AI developers and engineers for government
  • Innovation and research teams
  • Technical product managers investigating agentic AI systems
 14 Hours

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