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Course Outline

Foundations of AI Agents on Google Cloud

  • Understanding what AI agents are and how they differ from chatbots and standard AI applications.
  • Common business use cases for agents in enterprise environments.
  • Overview of Google Cloud services utilized in agent development.

Designing Agent Architecture

  • Core components of an agent: model, instructions, tools, memory, and workflow.
  • Selecting the appropriate level of agent capability for a business scenario.
  • Writing effective instructions and establishing basic guardrails.

Building an Agent with Vertex AI and Gemini

  • Preparing the Google Cloud environment for development.
  • Using Vertex AI and Gemini models to create a basic agent.
  • Testing prompts, responses, and simple agent behavior.

Connecting Agents to Tools and Data

  • Enabling tool use through APIs and function calling.
  • Connecting the agent to business data for grounded responses.
  • Enhancing reliability, relevance, and response quality.

Deploying and Operating Agents

  • Deployment options for agent solutions on Google Cloud.
  • Monitoring, logging, and basic evaluation of agent performance.
  • Security, access control, and responsible AI considerations.

Practical Workshop and Next Steps

  • Building a simple agent for a realistic business use case.
  • Reviewing design choices and improvement opportunities.
  • Planning next steps for pilot projects and further learning.

Requirements

  • Fundamental knowledge of cloud computing concepts and web applications.
  • Familiarity with APIs, JSON, and Google Cloud services or an equivalent cloud platform.
  • Basic programming experience in Python, JavaScript, or another modern language.

Audience

  • Developers seeking to build AI agents on Google Cloud.
  • Technical leads and solution architects investigating agent-based applications.
  • Data and AI professionals aiming for practical experience with Vertex AI agent capabilities.
 7 Hours

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