Basics of Streamlit

Utilizing the various components of Streamlit

Creating projects using Streamlit

Deploying Streamlit application

Basic understanding of python programing

Creating a web app and deploying the ML model is the toughest part since most the data science enthusiasts are not familiar with web dev. But Streamlit has made the job extremely easy. Being a Data Science enthusiast, I would like to share and contribute my learnings to the community!

This course introduces you to the basics of Streamlit library. Create professional-looking web applications with python without the knowledge of HTML/CSS.

The course introduces the basic elements of streamlit:

Adding Text and Data to your app

Plotting Graphs

Creating layout

Adding widgets

Chag the theme of your web application

Create a basic web app to understand how to combine streamlit and Machine learning models.

By the end of the course, you will be able to

create your own web app within few hours

create a user interface for your ML models

deploy your web application

Before you b, I would suggest you to brush up on your python skills.

I would also suggest coding along for better learning and understanding!

This course is for absolute bners who want to understand how streamlit works.

I have tried to keep things as simple as possible and therefore you might not find me using the best coding practices.

I prefer using VS Code for coding but feel free to use your favourite editor!

Bner python programmer and data science enthusiast






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