Develop Real-World Ai Agents In Gcp - Gemini, Adk, Mcp, A2a

Develop Real-World Ai Agents In Gcp - Gemini, Adk, Mcp, A2a
Published 7/2026
Created by K8s Point - Training House for GCP, AI & Kubernetes
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 76 Lectures ( 8h 32m ) | Size: 5.1 GB​

Build 6 Production-Ready, Full-Stack AI agents with Google ADK, Gen AI, MCP, A2A, RAG, Chainlit, Streamlit, Copilotkit
What you'll learn
Build Production Ready, Professional Looking, Real World AI agents from scratch - from Develop to Deploy - All in One
From Very Basic - Master the core concepts of modern AI agent development, including Google ADK, Gemini, MCP, A2A, RAG, tool calling and more
Agent 1 - Build your first conversational AI agent using Gemini, Google Gen AI SDK, and Chainlit
Agent 2 - Develop event-driven AI agents integrated using Google Gen AI SDK, Gemini with Google Cloud Storage, Cloud Functions, and other GCP services.
Agent 3 - Build your First AI Agent using Google ADK powered by Gemini with Chainlit UI at the Front. Understand Artifacts and Reasoning
Agent 4 - Develop Multi-Agent AI System with MCP integration. Agent to Database all in Natural Language, with a professional looking UI using Streamlit
Agent 5 - Create Multi-Agent application with Agent-to-Agent (A2A) Integration. RAG based knowledge retrieval with GCP Datastore
Agent 6 - Build modern AI applications with CopilotKit using the AG-UI Protocol for professional user experiences
Deploy AI agents locally and to Google Cloud Run using production-ready deployment practices. Understand and use Docker based deployment practice
Requirements
Very basic on GCP
Python Basic
Huge Amount on Interest in AI Agents
Description
Learn how to Develop & Deploy you Real World AI agents.
MasterGoogle Agent Development Kit (ADK) and theGoogle Gen AI SDK by building and deploying production-ready AI agents from scratch.
This hands-on course is designed fordevelopers who want practical experience with Google's latest agent framework. Instead of toy examples, you'll build6 real-world AI agents that demonstrate modern agentic AI architectures and enterprise integration patterns.
Also the course teaches how to use polished UI framework like Chainlit, Streamlit, Copilotkit with AI Agents
What You'll Learn
Build AI agents usingGoogle ADK
Develop applications with theGoogle Gen AI SDK and Gemini models
Createmulti-agent systems and agent orchestration workflows
ImplementModel Context Protocol (MCP) for tool and resource integration
BuildAgent-to-Agent (A2A) communication workflows
ImplementRetrieval-Augmented Generation (RAG) using enterprise knowledge sources
Integrate AI agents withSQL databases, APIs, and external services
Develop conversational agents with memory, state management, and streaming responses
Build user interfaces usingChainlit,Streamlit, andCopilotKit
Test and debug agents locally
Deploy production-ready applications toGoogle Cloud Run
Real-World Projects
Throughout the course, you'll build six end-to-end AI agent applications covering
Multi-agent collaboration
Tool calling and function execution
MCP server integration
RAG-based knowledge assistants
Database-backed AI applications
Human-like conversational agents
Production deployment on Google Cloud
Prerequisites
Basic Python programming
Familiarity with REST APIs
Basic understanding of Generative AI concepts (helpful but not required)
Whether you're an AI Engineer, Python Developer, Cloud Engineer, or Software Architect, this course will provide the practical skills needed to design, build, integrate, and deploy production-grade AI agents using Google's latest AI technologies.
Who this course is for
Anyone and Everyone - If you're fascinated with AI Agents and eager to create powerful Agentic AI applications - This is for you
Google Cloud professionals interested in deploying AI agents on Cloud Run and integrating with GCP services
Software engineers who want to learn modern Agentic AI concepts such as Multi-Agent Systems, MCP, A2A, and RAG.
Backend and Full-Stack developers building AI-powered applications with databases, APIs, and external tools.
Developers interested in integrating AI agents with modern UI frameworks such as Chainlit, Streamlit, and CopilotKit.
Anyone who has experimented with LLMs or chatbots and wants to build real-world, production-grade AI agent applications.
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