Livekit Voice AI Agents Master Class: Learn, Code & Deploy
Livekit Voice AI Agents Master Class: Learn, Code & Deploy
Published 6/2025
Duration: 2h 48m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 2.04 GB
Genre: eLearning | Language: English
Published 6/2025
Duration: 2h 48m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 2.04 GB
Genre: eLearning | Language: English
Build Low Latency real-time voice AI agents with LiveKit, OpenAI Realtime API, No SQL Database (Docker is not required!)
What you'll learn
- Understand the foundational components of a Voice AI Agent.
- Set up and deploy both frontend and backend services for a Voice AI application.
- Implement secure, scalable voice agent communication using LiveKit tokens and API routes.
- Customize and extend voice agent functionality for real-world use.
Requirements
- No Programming Experience Required. We Will Walk You Through Every Step.
Description
This hands-on masterclass teaches you how to build, customize, and deploy production-ready low latency voice AI agents using LiveKit, OpenAI Realtime API, No SQL Database. Docker desktop is not required!. Whether you’re a developer, Entrepreneur, AI tinkerer, or aspiring founder, this course gives you everything you need to create voice interfaces that talk, think, and take action in real time.
You’ll start by setting up a LiveKit Cloud account, integrating OpenAI Realtime API, and wiring up your assistant to real-time audio rooms. From there, you’ll connect a noSQL database to give your agent memory, then build a structured function-calling system so it can perform tasks like checking the weather, logging notes, or creating journal entries — all with your voice.
Next, you’ll explore the frontend and backend source code using React and Node.js, learn how to containerize your entire app using Docker, and deploy your codebase to the cloud with just one click..
By the end of this course, you’ll have:
Built and tested a full-stack voice agent powered by OpenAI Realtime API and LiveKit
Connected a noSQL database to store memory and user data
Deployed your agent’s backend and frontend using containers
Understood how to customize UI, function logic, and audio flow
STT & TTS solutions are available if you would like to use different LLM models or have more customization over the voice interaction with you AI Agent.
No prior WebRTC or voice AI experience is required — we walk you through every step, from templates to production.
Who this course is for:
- Students interested in Livekit & Pipecat Voice AI agents, low latency streaming, Voice Activity Detection, building and engineering voice ai assistants.
More Info