Agentic AI – Build AI Apps with Google Agent Development Kit

Learn how to Build & Deploy Enterprise Grade AI Agents using Google ADK – Practical based Learning – All Codes Included

What you’ll learn
From Develop to Deploy – Know everything you need to know on AI Agents. Build Enterprise grade AI Agents with Ease
A developer friendly approach to learn Google ADK. Completely practical based course with all codes included
If you know nothing about Agentic AI, not a problem, we will start from very basic
Understand how multi-agent-system works and create your own Multi-Agent-System Agents
Understand the Workflow Agents – Sequential, Parallel and Loop Agents – Know when to use which agent and why
Experiment with usage of Tools ( Ex – Google Search) with your agent
Use 3rd Party Tools with Agents – CrewAI and Langchain Tools
Multiple authentication options – Learn how to use Gemini API Key, Vertex AI or OpenAI / Anthropic for agent authentication setup
Deploy Your production ready Agents in Vertex AI Agent Engine or Cloud Run

Requirements
Very Basic Python
Eager to become AI Agents Champion

Description
Learn to build your first AI agent with easy to understand examples using Google Agent Development Kit. Google Agent Development Kit (ADK) is the enterprise-grade framework for building, testing, and deploying autonomous AI agents. Features of ADKÂ includes:Modular Open-Source Framework: ADK is a flexible, model-agnostic library (Python, TypeScript, Go, Java) designed to make agent building feel like standard software engineering.Specialized Agent Roles: It defines three primary agent types: LLM Agents (the reasoning “brains”), Workflow Agents (deterministic “managers”), and Custom Agents (the “specialists”).Advanced Orchestration: You can easily chain these agents into complex hierarchies, moving beyond single-task bots to full Multi-Agent Systems (MAS).The “Agent-as-a-Tool” Pattern: A unique design where a parent agent can treat another specialized agent as a simple tool, delegating tasks effortlessly.Multi-Modal Interactions: It natively supports bidirectional audio and video streaming, allowing users to interact with agents in real-time.Model Context Protocol (MCP) Support: It integrates with the MCP standard, giving your agents instant “hands and feet” to connect with hundreds of third-party apps and databases.Local Development UI: The adk web command launches a powerful browser-based dashboard to visualize agent reasoning and debug execution steps in real-time.Context & State Management: ADK handles the “heavy lifting” of session memory, allowing agents to remember user preferences across different conversation turns.Agent-to-Agent (A2A) Extension: It includes secure protocols for different agents to negotiate, hand off tasks, and share memory without losing context.Native Cloud Scaling: Once built, agents can be containerized and deployed directly to Vertex AI Agent Engine or Cloud Run for production-level scale.A complete course on Google ADK with step by step process on how to develop and deploy your Agent in Google Cloud. Learn from Basic to prod Level.Environment Setup ( Google Cloud / Local Desktop – laptop)Authenticate using Gemini Key / Vertex AI / 3rd Party ( Open AI / Anthropic)Learn to test your agent locally with adk web, adk run and adk api_server optionsUse built-in tools, custom tools, 3rd party toolsUse CrewAI and Langchain tools with ADKÂ AIÂ AgentsUse Agents as toolSub agent systemDevelop your Multi Agent SystemWorkflow agents – Sequential Agent / Parallel Agent / Loop AgentDeploy your agent using adk command line libraryDeploy your agent into Vertex AI Agent Engine, Cloud Run
Anyone who wants to become AI Agent Developer,Everyone who is in the world of AI

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