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StreamLit With Python || Zero to Hero
Rating: 3.0 out of 5(4 ratings)
40 students

StreamLit With Python || Zero to Hero

Webapps with StreamLit || Faster webapps with python StreamLit
Created byMeet Jethwa
Last updated 6/2025
English

What you'll learn

  • Python
  • Streamlit
  • Machine Learning
  • Heroku Deployment

Course content

9 sections15 lectures2h 50m total length
  • Introduction3:27
  • Installation2:32

Requirements

  • Python Programming

Description

Streamlit is an open source app framework in Python language. It helps us create web apps for data science and machine learning in a short time. It is compatible with major Python libraries such as scikit-learn, Keras, PyTorch, SymPy(latex), NumPy, pandas, Matplotlib etc. With Streamlit, no callbacks are needed since widgets are treated as variables. Data caching simplifies and speeds up computation pipelines. Streamlit watches for changes on updates of the linked Git repository and the application will be deployed automatically in the shared link.


This Course is designed to get started with python library called Streamlit for developing webapps on the go. It helps students to learn python and code some python projects into webapps with simple and few lines of code.

We will start from the scratch that what is StreamLit and the installation etc.

Requirements

Please ensure that you have the following:

  • Basic understanding of Programming

  • Python Programming Skills

  • Mid to high range PC/ Laptop

  • Windows 10/Ubuntu/Mac

What you’ll learn

  • Build a StreamLit Number Tracker App

  • Integrate Computer Vision into StreamLit

  • Implement Widgets, buttons and camera inputs

  • Python and StreamLit WebApp Development on Heroku

Are there any course requirements or prerequisites?

  • Python Programming Experience


Who this course is for:

  • Students who want to create presentable  web apps

  • Students who want to learn StreamLit and how to integrate it with amazing libraries in python

This is a practice along course. You can code along for maximum learning.

Who this course is for:

  • Python Developers
  • Web Application Developers
  • Developers looking to explore new stuff
  • Students interested to build their portfolio