Quiz Question 2

Which parameters are required to create a functioning LLM agent?

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Google: Build Your First Agent with Agent Development Kit (ADK)

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Google: Build Your First Agent with Agent Development Kit (ADK)

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This module transforms theory into practice by setting up your complete development environment. You’ll install Python, configure the Agent Development Kit (ADK), obtain API credentials, and create your first agent project, laying the essential foundation needed to start building agents.

Exercise 1: Understand your setup Exercise 2: Quiz Question 1 Exercise 3: Quiz Question 2

This module decodes the anatomy of an agent via the four core parameters that define its identity and behavior. You’ll learn to distinguish between description (what other agents see) and instruction (how this agent acts) and to write instructions that shape agent personality and capabilities.

Exercise 1: Define your agent's identity Exercise 2: Hands-on: Transform your agent Exercise 3: Quiz Question 1 Exercise 4: Quiz Question 2

Bài tập hiện tại

This module expands your agent execution toolkit beyond the web interface, introducing three distinct deployment methods: Terminal commands for quick testing, API servers for production deployments, and programmatic execution for integration into larger applications.

Exercise 1: Three deployment methods Exercise 2: Quiz Question 1 Exercise 3: Quiz Question 2

This module introduces a code-free alternative to defining agents through YAML configuration files. You’ll learn when declarative YAML configurations provide advantages over Python code for agent definition and how to create and manage YAML-based agents.

Exercise 1: Two ways to define agents Exercise 2: Quiz Question 1 Exercise 3: Quiz Question 2

In just 75 minutes, you’ve transformed from understanding agent concepts to actually building and running your own AI agents. You’ve set up a complete development environment, created agents from scratch, experimented with different execution modes, and learned both Python code and YAML configuration approaches.This is no small feat. You've taken the critical step from theory to practice.

Exercise 1: Reading list