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Course Outline
Core Foundations of AI Agents on Google Cloud
- Defining AI agents and distinguishing them from chatbots and conventional AI applications.
- Identifying common business use cases for agents in enterprise settings.
- Survey of Google Cloud services utilized in agent development.
Architecting AI Agents
- Essential agent components: models, instructions, tools, memory, and workflows.
- Selecting the appropriate agent capability level for specific business scenarios.
- Crafting effective instructions and establishing basic guardrails.
Creating Agents with Vertex AI and Gemini
- Configuring the Google Cloud environment for development.
- Utilizing Vertex AI and Gemini models to create foundational agents.
- Testing prompts, responses, and basic agent behaviors.
Integrating Agents with Tools and Data
- Facilitating tool usage through APIs and function calling.
- Linking agents to business data to ensure grounded responses.
- Enhancing reliability, relevance, and the quality of responses.
Deploying and Managing Agents
- Exploring deployment options for agent solutions on Google Cloud.
- Monitoring, logging, and conducting basic performance evaluations.
- Addressing security, access control, and responsible AI considerations.
Hands-On Workshop and Future Directions
- Constructing a simple agent for a realistic business scenario.
- Evaluating design choices and identifying areas for improvement.
- Planning subsequent steps for pilot projects and continued learning.
Requirements
- Fundamental knowledge of cloud computing principles and web applications.
- Experience with APIs, JSON, and Google Cloud services or comparable cloud platforms.
- Basic programming proficiency in Python, JavaScript, or another contemporary language.
Target Audience
- Developers aiming to construct AI agents on Google Cloud.
- Technical leads and solution architects investigating agent-based application architectures.
- Data and AI specialists seeking practical experience with Vertex AI agent features.
7 Hours
