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Course Outline
Foundations of Agentic AI with Gemini 3
- Agentic reasoning and the execution of autonomous tasks
- Unique capabilities of Gemini 3 supporting agent workflows
- Enterprise use cases necessitating autonomous agents
Navigating the Antigravity Development Environment
- Core concepts, architectural overview, and toolset
- Project and environment management
- Execution and monitoring of agent runs
Architecture for Autonomous Agents
- Structuring tasks and workflows to enable autonomy
- Implementing multi-step reasoning and planning chains
- Designing secure and controlled action loops
Code Generation and Tool Utilization in Antigravity
- Enabling agents to write and refine code
- Delegating tasks to system tools and APIs
- Managing tool permissions and operational capabilities
Leveraging Multimodal Capabilities in Gemini 3
- Processing images, documents, and structured data
- Synthesizing multiple modalities for complex planning
- Extracting insights to drive autonomous decision-making
Enterprise System Integration for Agents
- Connecting Antigravity to external APIs
- Interacting with cloud services and databases
- Constructing end-to-end automated business workflows
Refining and Assessing Agent Performance
- Enhancing reliability and managing output variability
- Debugging and optimizing agent actions
- Performance optimization, scaling, and workload orchestration
Ethical Use, Safety, and Governance
- Oversight of agent autonomy within enterprise contexts
- Implementing safety rules, constraints, and governance controls
- Auditing agent decisions and ensuring transparency
Conclusion and Future Directions
Requirements
- A solid understanding of advanced AI concepts
- Practical experience in software development and cloud environments
- Familiarity with prompt engineering or model orchestration
Target Audience
- AI developers
- Software engineers
- R&D teams
21 Hours
Testimonials (1)
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