Build with AI: Production-Ready AI Apps with Gradio
1h 20mAdvanced2025-07-17
Authors
Deepak Goyal
Course details
Did you know you can leverage AI to build apps in Gradio, the popular machine learning model demo tool? In this course, designed for developers, instructor Deepak Goyal shows you how to move beyond simple Gradio apps and build fully functional, production-grade AI applications. Explore Gradio Blocks, state management, event handling, and authentication, as well as how to integrate with LangChain, OpenAI, Pinecone, and APIs to power advanced use cases. By the end of this course, you’ll be prepared to implement a scalable, interactive app with Docker and CI/CD. Whether deploying to Azure, AWS, or elsewhere, this course equips you with the skills you need to make your AI apps robust, secure, and enterprise-ready.
Learning objectives
Create modular and scalable Gradio interfaces using advanced Blocks.
Handle UI events and build multi-step user workflows.
Secure Gradio apps with authentication and manage app state.
Connect Gradio with LLMs, LangChain, and external APIs.
Dockerize and deploy Gradio apps using CI/CD and cloud platforms.
Learning objectives
Create modular and scalable Gradio interfaces using advanced Blocks.
Handle UI events and build multi-step user workflows.
Secure Gradio apps with authentication and manage app state.
Connect Gradio with LLMs, LangChain, and external APIs.
Dockerize and deploy Gradio apps using CI/CD and cloud platforms.
Skills covered
TelecommunicationsFull-Stack Web DevelopmentArtificial Intelligence FoundationsArtificial Intelligence (AI)Web DevelopmentNetwork and System AdministrationOne-Off
Concepts
0. Introduction
- 01 - Advanced Gradio
- 02 - What you should know
1. Advanced Gradio Concepts
- 03 - Real-world use cases
- 04 - Building with Gradio blocks for complex UIs
- 05 - Event handling - Triggers, updates, and interactions
- 06 - Multi-step workflows and pipelines
2. Enhancing the User Experience
- 07 - Adding authentication to your Gradio app
- 08 - Using Gradio with LangChain and LLMs
- 09 - Upload, preview, and inference pattern
- 10 - Advanced API integration
3. App Intelligence and Monitoring
- 11 - State management and persistence
- 12 - Adding feedback mechanisms to your apps
- 13 - Logging, monitoring, and error tracking
4. Production Deployment
- 14 - Deploying to production with CI CD (such as GitHub Actions)
5. Final Project
- 15 - Project - Build a real-world app from scratch
- 16 - Project solution walk-through
Conclusion
- 17 - Next steps