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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
Testimonials (1)
Trainers can answer all questions and accept any queries
