Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Agentic AI for Government
- Defining agentic AI and its relationship to traditional AI systems for government operations
- Overview of reasoning, memory, and goal-driven architectures in the context of public sector applications
- Key use cases and industry applications relevant to government agencies
Core Concepts and Design Patterns for Government Use
- The agent loop: perception, reasoning, and action in governmental processes
- Single-agent vs. multi-agent systems for efficient public service delivery
- Environment interaction and tool invocation for government-specific tasks
Prompt Engineering Fundamentals for Government Applications
- Designing effective prompts for reasoning and task decomposition in governmental workflows
- Using examples, constraints, and roles to enhance control over government AI systems
- Systematically debugging and iterating prompts for optimal performance in public sector contexts
Building Simple Agentic Workflows for Government Use
- Implementing an agent loop in Python for government projects
- Integrating with APIs and simple tools to support government operations
- Managing agent state and memory for reliable public sector applications
Responsible Design and Safety Practices for Government AI
- Ethical considerations and responsible use of agents in government settings
- Addressing bias, ensuring transparency, and maintaining accountability in government AI systems
- Implementing access control, data protection, and content safety measures for government applications
Hands-on Project: Designing a Responsible Agent for Government Use
- Defining the problem scope and objectives for a government project
- Developing the prompt and control logic to meet governmental needs
- Testing, refining, and evaluating agent behavior to ensure compliance with government standards
Summary and Next Steps for Government Implementation
Requirements
- A fundamental understanding of artificial intelligence or machine learning concepts for government applications.
- Familiarity with Python syntax and scripting for government projects.
- Experience working with data or API-based applications in a public sector context.
Audience
- Data scientists new to agentic AI development for government use.
- Junior machine learning engineers exploring applied agent architectures for government initiatives.
- Technology managers seeking to understand agent design and safety principles for government operations.
14 Hours
Testimonials (3)
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Autonomous Decision-Making with Agentic AI
practical exercises
