Enhancing AI Agents with Agentic Capabilities Training Course
Agentic AI enhances traditional artificial intelligence (AI) agents by enabling adaptive decision-making, autonomous goal-setting, and self-improving behavior.
This instructor-led, live training (online or onsite) is designed for intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications for government use.
By the end of this training, participants will be able to:
- Understand the principles of agentic AI and autonomous decision-making.
- Implement goal-driven AI agents with self-optimization techniques.
- Integrate multi-agent collaboration for complex problem-solving.
- Enhance AI-human interaction through adaptive user experiences.
- Deploy agentic AI models in real-world applications for government.
Format of the Course
- Interactive lecture and discussion.
- Extensive exercises and practice sessions.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact Govtra to arrange.
Course Outline
Introduction to Agentic AI for Government
- Defining agentic capabilities in artificial intelligence (AI)
- Key distinctions between traditional and agentic AI agents
- Use cases of agentic AI across various sectors, including public services
Developing Goal-Driven AI Agents for Government
- Understanding autonomous goal-setting and prioritization in government applications
- Implementing reinforcement learning to enhance self-improvement of AI agents
- Fine-tuning AI agent behaviors based on feedback loops for improved performance
Multi-Agent Collaboration and Coordination for Government
- Building AI agents that collaborate and communicate effectively within public sector workflows
- Task delegation and role assignment in agentic systems to optimize resource management
- Real-world examples of multi-agent teamwork in government operations
Adaptive AI-Human Interaction for Government
- Personalizing AI responses based on user behavior to enhance citizen engagement
- Context-awareness and dynamic decision-making to improve service delivery
- Designing user experiences (UX) for intelligent and responsive AI agents in government services
Deploying Agentic AI in Government Applications
- Integrating agentic AI with APIs and third-party tools to support public sector initiatives
- Ensuring scalability and efficiency in AI deployments for government operations
- Case studies on successful agentic AI implementations within government agencies
Ethical Considerations and Challenges for Government
- Balancing autonomy with control in AI agents to maintain public trust
- Addressing AI biases and ethical concerns in government applications
- Regulatory frameworks for autonomous AI systems to ensure compliance and accountability
Future Trends in Agentic AI for Government
- Emerging advancements in AI autonomy and their implications for public sector innovation
- Expanding agentic capabilities with new technologies to enhance government services
- Predictions for AI-driven automation and decision-making in government operations
Summary and Next Steps for Government
Requirements
- Fundamental knowledge of artificial intelligence (AI) agents and automation
- Proficiency in Python programming
- Familiarity with API-based AI integrations
Audience
- AI developers enhancing autonomous systems for government
- Automation engineers optimizing AI-driven workflows for government operations
- User experience (UX) designers improving human-agent interactions for government services
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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