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Duration 21 hours
Course Outline
Foundations of Agentic AI with Gemini 3
- Agentic reasoning and the execution of autonomous tasks
- Distinctive Gemini 3 capabilities for agent-based workflows
- Enterprise use cases necessitating autonomous agents
Navigating the Antigravity Development Environment
- Core architectural concepts and available toolsets
- Project and environment management strategies
- Execution and monitoring of agent operations
Architecting Autonomous Agents
- Structuring tasks and workflows to enable autonomy
- Implementing multi-step reasoning and planning chains
- Creating safe and controlled action loops
Code Generation and Tool Integration in Antigravity
- Enabling agents to write and refine code
- Delegating tasks to system tools and external APIs
- Managing tool permissions and operational capabilities
Leveraging Multimodal Capabilities with Gemini 3
- Processing images, documents, and structured data
- Integrating modalities for complex planning scenarios
- Extracting insights to drive autonomous decision-making
Enterprise System Integration
- Connecting Antigravity to external API endpoints
- Interacting with cloud services and database systems
- Building end-to-end automated business processes
Agent Optimization and Evaluation
- Enhancing reliability and managing output variability
- Debugging and refining agent actions
- Performance tuning, scaling, and workload orchestration
Responsible AI, Safety, and Governance
- Oversight of agent autonomy in enterprise settings
- Establishing safety rules, constraints, and governance controls
- Auditing decision paths and ensuring transparency
Conclusion and Future Directions
Requirements
- A solid grasp of advanced AI concepts
- Proficiency in software development and cloud environments
- Familiarity with prompt engineering or model orchestration
Target Audience
- AI Developers
- Software Engineers
- R&D Teams
Testimonials (1)
Flow , vibe and topic on presentation