Building Voice-Driven Apps with Gemini
This course introduces students to the development of an AI-powered voice interview system using Python and Google’s Gemini Live API. Learners explore how prerecorded audio responses are captured, processed, and sent to an AI model, as well as how the model produces synthesized audio replies that simulate an automated interviewer.
This course includes.
Curriculum & lectures.
+ 01 Introduction 2 lectures
+ 02 Building Our AI Interviewer 6 lectures
About this course.
The course focuses on building a turn-based interaction flow, where recorded audio segments are interpreted by Gemini and used to guide a structured, multi-question interview.
Students work with key components of the system, including microphone recording with sounddevice, audio packaging, asynchronous communication with the Gemini Live API, and the management of multi-turn conversational context. They also examine how the system stores transcripts, generates AI-driven feedback, and produces a final summary evaluating communication, technical skills, and behavioral responses.
By completing the project, learners gain hands-on experience creating a functional voice-driven application and develop a practical understanding of how Gemini can support intelligent, context-aware interactions.
Ready to start building?
This course introduces students to the development of an AI-powered voice interview system using Python and Google’s Gemini Live API. Learners explore how prerecorded audio responses are captured, processed, and sent to an AI model, as well as how the model produces synthesized audio replies that simulate an automated interviewer.