Course Outline

Introduction to Generative AI and Agentic AI for Government

  • Overview of Generative AI and Agentic AI
  • Key differences and complementary aspects of these technologies
  • Application scenarios and emerging trends across various sectors, including public service

Generative AI Architecture and Tools for Government Use

  • Advanced transformer models: GPT, LLaMA, Claude, and others
  • Techniques in fine-tuning versus 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 Operations

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

Understanding Agentic AI for Government Applications

  • Definition and development of agentic AI
  • Architectural components: planning, memory, tool integration, self-reflection
  • Prominent frameworks: AutoGPT, BabyAGI, CrewAI, LangGraph

Designing and Deploying Autonomous Agents for Government Services

  • Methods for setting goals and decomposing tasks
  • Integrating tools and APIs (search, memory, code) to support government operations
  • Strategies for multi-agent coordination and human-in-the-loop supervision in public sector applications

Use Cases and Implementation Scenarios for Government

  • Differentiating content generation from task orchestration
  • Enhancing enterprise productivity, customer support, and data extraction in government agencies
  • Ensuring responsible and secure implementation of AI technologies for government use

Summary and Next Steps for Government Implementation

Requirements

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

Audience

  • AI developers and engineers for government projects
  • Innovation and R&D teams within government agencies
  • Technical product managers exploring agentic AI systems for government use
 14 Hours

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