Voice for AI Agents and Applications
by DeepLearning.AI
Add a voice layer to the agent you already have — including outbound phone calls.
Overview
A free DeepLearning.AI short course taught by Ashwyn Sharma, CEO and co-founder of Vocal Bridge, running about an hour and a half across eight video lessons. Sharma brings roughly a decade of production voice AI from Meta AI, Salesforce and Otter.ai, and Vocal Bridge is an AI Fund company co-founded with DeepLearning.AI. The course is organised around the central tradeoff in voice agents: low-latency speech-to-speech models lack reliability, while transcribe-think-speak pipelines are more capable but too slow to feel conversational. The architecture taught here is a two-agent split — a foreground agent that converses with the user in real time to hold latency down, and a background agent that runs the actual agentic workflow, reasons, applies guardrails and calls tools. You build three things: a voice-interactive tic-tac-toe game that establishes the real-time loop, a voice layer added to an existing text agent with minimal changes to its prompts, RAG pipeline or tools, and an agent that places outbound phone calls. The final section covers voice evaluation — scoring an agent's recorded calls to surface failure modes and catch regressions before production — which is the part most voice tutorials omit entirely. The practical claim worth testing is that adding voice to an agent you already have should be additive rather than a rewrite. No prior experience with voice APIs is assumed, only basic Python.
At a Glance
- Topic
- Agentic
- Level
- Beginner
- Format
- Course
- Cost
- Free
- Duration
- ~1.5 hours (1h 26m), 8 video lessons, self-paced
- Provider
- DeepLearning.AI
- Hands-on
- Yes — code/exercises
- Certificate
- Available
What You’ll Learn
- ✓Explain the latency-versus-intelligence tradeoff in voice agent architectures
- ✓Split a voice agent into real-time foreground and reasoning background agents
- ✓Build a voice-interactive application driven by a real-time conversational loop
- ✓Add a voice layer to an existing text agent with minimal code changes
- ✓Keep existing prompts, RAG pipelines and tools intact when adding voice
- ✓Build an agent that places outbound phone calls to real numbers
- ✓Score recorded agent calls to surface failure modes before production
Highlights
- •Taught by a founder with a decade of production voice AI at Meta AI, Salesforce and Otter.ai
- •Teaches voice as a layer over your existing agent rather than a from-scratch rebuild
- •Includes voice evaluation — scoring real calls for regressions — which most voice tutorials skip
- •Covers outbound telephony, not just in-browser microphone demos
- •About 90 minutes and free to audit, with only the certificate behind PRO membership
Who It’s For
Best For
- ✓Developers who already have a working text agent and want voice
- ✓Product engineers prototyping voice interfaces for existing applications
- ✓Teams evaluating voice agents for customer-facing phone workflows
- ✓Python developers with no prior voice API experience
Prerequisites
- •Basic familiarity with Python
- •No prior experience with voice APIs or telephony is required
FAQ
What is Voice for AI Agents and Applications?
A 90-minute, free DeepLearning.AI course taught by Vocal Bridge CEO Ashwyn Sharma on adding voice to agents you already have. It teaches the foreground/background agent split that keeps conversation latency low while a slower agent reasons and calls tools, then walks through three builds — a voice-driven game, a voice layer over an existing text agent, and an outbound calling agent — plus evaluating recorded calls before production.
Is Voice for AI Agents and Applications free?
Voice for AI Agents and Applications is free to access.
What level is Voice for AI Agents and Applications for?
Voice for AI Agents and Applications is aimed at a beginner audience. Recommended background: Basic familiarity with Python, No prior experience with voice APIs or telephony is required.
How long does Voice for AI Agents and Applications take?
Expect roughly ~1.5 hours (1h 26m), 8 video lessons, self-paced. Most learners work through it at their own pace.
What will I learn from Voice for AI Agents and Applications?
You'll learn: Explain the latency-versus-intelligence tradeoff in voice agent architectures; Split a voice agent into real-time foreground and reasoning background agents; Build a voice-interactive application driven by a real-time conversational loop; Add a voice layer to an existing text agent with minimal code changes; Keep existing prompts, RAG pipelines and tools intact when adding voice; Build an agent that places outbound phone calls to real numbers; Score recorded agent calls to surface failure modes before production.
Topics
Sources
This page was written from 3 sources, 1 on domains other than deeplearning.ai.