Voice AI Engineer

Three tracks in sequence: ML & AI Engineering, then Agentic AI Engineering, then Voice & Conversational AI Engineering. Real-time voice is an agent problem with a latency budget, so the agent work comes first and the voice track builds on it.

3 courses · Intermediate

The path, in order

  1. ML & AI Engineering — From Python basics to production ML and AI systems
  2. Agentic AI Engineering — Design, build, evaluate, and deploy production-grade AI agents
  3. Voice & Conversational AI Engineering — Build, deploy, and optimize production-grade real-time voice AI agents

Optional foundations, if you are starting from zero

The path assumes you can already write Python. If you cannot, take these first.

  1. Programming & CS Foundations — How to think like a programmer, from zero, before any AI or math content
  2. Engineering Practices & Tooling — The Missing Semester for AI Engineers: git, the command line, APIs and the craft real jobs assume you have
  3. Data Analysis & Visualization — pandas, NumPy, and the daily skill of turning real messy data into an answer

What you become

An engineer who can ship a real-time voice assistant: speech in, conversational state, tool calls, interruption handling, and a latency budget you can defend.

Roles this path prepares you for

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