Course Outline

Foundations of AI Agents on Google Cloud

  • 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 used in agent development

Designing Agent Architecture

  • Core components of an agent: model, instructions, tools, memory, and workflow
  • Choosing the right level of agent capability for a business scenario
  • Writing effective instructions and setting 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 with APIs and function calling
  • Connecting the agent to business data for grounded responses
  • Improving 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

  • A basic understanding of cloud computing concepts and web applications
  • Familiarity with APIs, JSON, and Google Cloud services or a similar cloud platform
  • Basic programming experience in Python, JavaScript, or another modern language

Audience

  • Developers who want to build AI agents on Google Cloud
  • Technical leads and solution architects exploring agent-based applications
  • Data and AI practitioners who want practical experience with Vertex AI agent capabilities
 7 Hours

Number of participants


Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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