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Course 2: Agentic Workflows with ADK

Course Overview

This course teaches you to design, implement, and deploy multi-agent systems using ADK and Vertex AI Gemini. You'll master 8 core agentic workflow patterns through hands-on exercises and apply them in a comprehensive capstone project.

Learning Path

Prerequisites

  • Python programming experience
  • Basic understanding of LLMs and APIs
  • Google Cloud Platform familiarity

Modules

Module Focus Duration Key Skills
Lesson 1 Workflow Analysis & ADK Basics 60 min Task decomposition, agent coordination
Lesson 2 Code-First Workflow Modeling 45 min Agent classes, data flow design
Lesson 3 ADK Implementation Patterns 60 min SequentialAgent, ParallelAgent, Gemini integration
Lesson 4 Prompt Chaining Pattern 45 min Sequential validation, context passing
Lesson 5 Routing Pattern 45 min Input classification, intelligent routing
Lesson 6 Parallelization Pattern 45 min Concurrent execution, result aggregation
Lesson 7 Evaluator-Optimizer Pattern 60 min Iterative refinement, quality loops
Lesson 8 Orchestrator-Workers Pattern 60 min Dynamic delegation, multi-agent systems

Capstone Project

AI Research Assistant - Build a comprehensive research agent that demonstrates all 8 workflow patterns in an integrated system for automated knowledge synthesis.

Setup Instructions

1. Environment Setup

# Clone the course repository
git clone [repository-url]
cd course-2-agentic-workflows-adk

# Install dependencies
pip install -r requirements.txt

# Set up GCP authentication
gcloud auth application-default login
gcloud config set project YOUR_PROJECT_ID

# Enable required APIs
gcloud services enable aiplatform.googleapis.com

2. Verify Installation

# Test ADK availability
python -c "from google.adk.agents import LlmAgent; print('ADK ready!')"

# Test Vertex AI access
python -c "from google import genai; print('Vertex AI ready!')"

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