Gain insights into building robust front-end Python web applications with Streamlit. Explore integrating Python libraries, creating visualizations, interactive widgets, and deploying on Streamlit cloud.

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Python is the premier programming language for data science and machine learning, but its native strengths for back-end development can leave developers scrambling for a front-end solution. Enter Streamlit, a robust open-source library for developing front-end applications with Python.

This course is a comprehensive introduction to building Streamlit applications integrated with different Python libraries. You’ll be walked through successive projects to create visualizations, display interactive widgets, and customize layouts. You won’t just display data but work on data transformations using Streamlit interfaces and become familiar with basic functionality for native Python applications like caching and placeholders. You’ll wrap up with deploying your application using the Streamlit cloud.

By the end of this course, you’ll be ready to give your Python-based data science and machine learning applications robust user interfaces using Streamlit.

Building the Frontend of Python Web Applications with Streamlit

## Final words

Congratulations! You have finally finished the Building Web Apps/UIs with Python and Streamlit course. Go ahead and give yourself a round of applause!

We hope that this course met your expectations, and you were able to learn about the Streamlit web interface and understand the concepts and topics covered in this course. Now, you can convert any Python app to a web interface and also deploy it using Streamlit.

## Feedback
We tremendously appreciate you being a part of the Educative learning community. We look forward to your feedback, comments, concerns, and questions. Feel free to contribute to the codebase or drop us an [email](https://www.educative.io/contactUs)!






# Final words

Congratulations! You have finally finished the Building Web Apps/UIs with Python and Streamlit course. Go ahead and give yourself a round of applause!

We hope that this course met your expectations, and you were able to learn about the Streamlit web interface and understand the concepts and topics covered in this course. Now, you can convert any Python app to a web interface and also deploy it using Streamlit.

# Feedback
We tremendously appreciate you being a part of the Educative learning community. We look forward to your feedback, comments, concerns, and questions. Feel free to contribute to the codebase or drop us an [email](https://www.educative.io/contactUs)!






Final words about building Web Apps/UIs with Python and Streamlit.

Conclusion

Introduction

Build a UI for a Model Using Streamlit

Build a Classification Web App using Streamlit and Sklearn

Build a Streamlit App to Scrape Github Profiles

Build a Web App to Transcribe Audio using Python and AssemblyAI

Build a Web App to Generate and Display a Word Cloud of Trending

Build a Web App to Download YouTube Videos in 30 Lines of Code

Deploy Streamlit Apps

Wrapping Up

Conclusion

Final words

Feedback