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Course Outline
Understanding Agentic AI with Gemini 3
- Agentic reasoning and autonomous task execution.
- Unique capabilities of Gemini 3 for agent workflows.
- Enterprise scenarios that benefit from autonomous agents.
Exploring the Antigravity Development Environment
- Core concepts, architecture, and available toolsets.
- Project and environment management.
- Executing and monitoring agent runs.
Designing Autonomous Agents
- Structuring tasks and workflows for autonomy.
- Multi-step reasoning and planning chains.
- Designing safe and controlled action loops.
Coding and Tool Use in Antigravity
- Enabling agents to write and refine code.
- Delegating tasks to system tools and APIs.
- Managing tool permissions and capabilities.
Multimodal Agent Capabilities with Gemini 3
- Processing images, documents, and structured data.
- Combining modalities for complex planning.
- Extracting insights for autonomous decision-making.
Integrating Agents with Enterprise Systems
- Connecting Antigravity to external APIs.
- Interacting with cloud services and databases.
- Building end-to-end automated business workflows.
Optimizing and Evaluating Agent Behavior
- Improving reliability and controlling variability.
- Debugging and refining agent actions.
- Performance, scaling, and workload orchestration.
Responsible Use, Safety, and Governance
- Managing agent autonomy in enterprise contexts.
- Safety rules, constraints, and governance controls.
- Auditing agent decisions and maintaining transparency.
Summary and Next Steps
Requirements
- A solid understanding of advanced AI concepts.
- Experience in software development and cloud environments.
- Familiarity with prompt engineering or model orchestration.
Target Audience
- AI developers.
- Software engineers.
- Research and development (R&D) teams.
21 Hours
Testimonials (1)
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