Course Description:
This course covers the essential communication protocols for AI systems, enabling interoperability, integration, and coordinated workflows. Learners will explore how to connect AI models to diverse data sources, facilitate agent-to-agent communication, and standardize information exchange across teams and platforms.

Lecture 1: MCP (Model-Context Protocol)
Understand how MCP connects AI models to external data sources using secure, structured communication. Learn about pre-built integrations, HTTPS-based capabilities, and client-server setups.

Key Objectives:

• Connecting AI models to data sources
• Pre-built integrations
• HTTPS with JSON-based capabilities
• Client-server architecture

Lecture 2: A2A (Agent to Agent Protocol)
Learn how AI agents communicate and coordinate across ecosystems, with a focus on Google integration and automation. Explore agent identity, target cards, and cross-platform workflows.

Key Objectives:

• Google ecosystem integration
• Target cards and agent identity
• Cross-platform coordination
• Gmail and Google Drive automation

Lecture 3: ACP (Agent Communication Protocol)
Discover how ACP enables framework-agnostic communication between teams and agents. Learn standards for language, formats, and effective collaboration.

Key Objectives:

• Cross-team collaboration
• Framework-agnostic communication
• Language and format standards