Date d'abonnement : 2022
Customer Experience Agent Studio: Fundamentals
Earned mars 4, 2026 EST
Agent Fundamentals
Earned jan. 28, 2026 EST
Optimize Agent Behavior
Earned jan. 28, 2026 EST
Build Your First Agent with Agent Development Kit (ADK)
Earned jan. 28, 2026 EST
Build a Certification Study Guide: PMLE
Earned déc. 21, 2025 EST
[DEPRECATED] Webhook fundamentals
Earned oct. 29, 2025 EDT
This course aims to equip conversational designers and builders with the concepts and practical skills to design, build, and test sophisticated, multi-agent, and multimodal Customer Experience agents using Customer Experience Agent Studio (CX Agent Studio).
AI Agents represent a major shift beyond traditional large language models (LLMs): instead of simply generating text-based solutions, they can also act autonomously to execute them. This course introduces the fundamentals of AI Agents, how they differ from LLM APIs, and where they add value in the real world. Based on Google’s agents whitepaper, it provides the theoretical foundation needed before writing your first lines of agent code—ideal for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior (and not just text generation). Join the community forum for questions and discussions.
You’ve built your first agent—now it’s time to take it further. In this course, you’ll advance your skills by learning how to turn a basic AI agent into a sophisticated, precise assistant—applying advanced instructions, model selection, planning capabilities, and structured output patterns. Join the community forum for questions and discussions
Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK). In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior, taking what you learned in course 1 and applying it to working code.
Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.
In this course, you will learn the important role that different types of webhooks play in Dialogflow CX development, and how to effectively integrate them into your routine configuration of a Virtual Agent.