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Course Outline
Foundations of AI Agents on Google Cloud
- Understanding what AI agents are and how they distinguish from chatbots and conventional AI applications
- Exploring common enterprise use cases for agent deployment
- Reviewing the Google Cloud services utilized in agent development
Agent Architecture Design
- Identifying key agent components: models, instructions, tools, memory, and workflows
- Selecting appropriate agent capability levels for specific business scenarios
- Crafting effective instructions and establishing basic safety guardrails
Building Agents with Vertex AI and Gemini
- Setting up the Google Cloud environment for development tasks
- Utilizing Vertex AI and Gemini models to create a foundational agent
- Testing prompts, responses, and basic agent behavior
Integrating Agents with Tools and Data
- Enabling tool usage through APIs and function calling
- Linking agents to business data to ensure grounded responses
- Enhancing reliability, relevance, and overall response quality
Deploying and Managing Agents
- Examining deployment options for agent solutions on Google Cloud
- Implementing monitoring, logging, and basic performance evaluation
- Addressing security, access control, and responsible AI considerations
Practical Workshop and Future Steps
- Constructing a simple agent for a realistic business scenario
- Evaluating design decisions and identifying areas for improvement
- Planning next steps for pilot projects and continued learning
Requirements
- A foundational understanding of cloud computing principles and web applications
- Proficiency with APIs, JSON, and Google Cloud services or comparable cloud platforms
- Basic coding experience in Python, JavaScript, or another contemporary programming language
Target Audience
- Developers seeking to create AI agents on Google Cloud
- Technical leads and solution architects evaluating agent-based application architectures
- Data and AI professionals interested in gaining practical experience with Vertex AI agent capabilities
7 Hours
