Conversational AI has transformed customer engagement, with 45% of support queries now resolved automatically by advanced agents. This Short Course was created to help Software Development professionals accomplish rapid deployment of intelligent virtual assistants using Google's enterprise-grade Dialogflow CX platform. By completing this course, you'll be able to design intent structures that achieve 85%+ match accuracy, diagnose mis-routed utterances through transcript analysis, calculate critical NLU performance KPIs, and build webhook integrations that retrieve live data in under 1 second—capabilities you can deploy to staging tomorrow.

By the end of this course, you will be able to: ● Apply intent-classification heuristics to build five new intents that achieve ≥85% training-phrase match accuracy in Dialogflow CX ● Analyze one week of chat logs, isolate three mis-routed utterances, and correct them by refining entities or training phrases ● Evaluate agent quality by exporting fulfillment diagnostics, calculating NLU accuracy, latency, and human-handoff rate, and recommending two optimization actions ● Create a secure webhook (Node.js or Python) that calls an external REST API and returns dynamic data to the user in ≤1 second round-trip (Create) This course is unique because it combines hands-on Dialogflow CX development with diagnostic methodologies for measuring and improving conversational agent performance, bridging the gap between building chatbots and deploying enterprise-grade AI systems that meet production SLAs. To be successful in this project, you should have a background in API integration, basic Python or Node.js programming, and software development practices at CB2 intermediate-level expertise.