Use Conversational Language Understanding with Language Studio
About this guide
Scenario
Increasingly, we expect computers to be able to use AI to understand natural language commands, either spoken or typed. For example, you might want a home automation system to control devices in your home by using voice commands such as “switch on the light” or “put the fan on.” AI-powered devices can understand these commands and take appropriate action.
In this guide, you will use Language Studio to create and test a project that sends instructions to devices such as lights or fans. You’ll use the capabilities of the Conversational Language Understanding service to configure your project.
Tasks and Job Skills
- Create a Language resource
- Create a Conversational Language Understanding App
- Create intents, utterances, and entities
- Train the model
- Deploy and test the model
Career Connections
The Cloudguides in this series provide a foundational understanding of Azure AI services and are valuable to anyone interested in pursuing a career in AI or expanding their knowledge in this growing field.
The skills developed in this series can help opens doors to roles like entry-level AI Engineer, Data Scientist (with AI focus), Cloud Architect (with AI focus), and Business Analyst (with AI focus).
As of January 2025, AI-focused roles in the U.S. offer competitive salaries, with AI Engineers starting at around $108K and reaching $128K after five years, Data Scientists earning between $90K–$130K initially and $123K with experience, Cloud Solutions Architects starting at $110K and rising to $160K, Business Analysts beginning at $55K and reaching $131K, while IT professionals with AI interest typically start at $80K and can earn $100K–$150K or more depending on specialization and demand. Please note that these figures are approximate, derived from online sources, and can vary based on factors such as location, industry, and company size.
