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Streamlit Bootcamp
Rating: 4.4 out of 5(205 ratings)
25,505 students

Streamlit Bootcamp

Build beautiful web apps for your Data Science and Machine Learning projects in a fast and easy way using Streamlit.
Created byRaj Chhabria
Last updated 1/2023
English

What you'll learn

  • Building complete Web Applications from Scratch using Streamlit.
  • Develop Strong Skills about ALL Streamlit's Basic and Advanced Features.
  • Use Streamlit to create Data Science and Machine Learning Web Apps.
  • Learn to build beautiful User Interface for your ML models using Streamlit.

Course content

8 sections • 29 lectures • 2h 13m total length

  • Introduction and Welcome1:31
  • Course Overview and Key Learning Outcomes3:32

    Explore core and advanced Streamlit concepts—from text and data display to charts, widgets, media, and layouts—culminating in projects like insurance premium predictor, calories burned calculator, and stock market index prediction.

  • Installation and Setup1:04

Requirements

  • Basic Knowledge of Python Programming Language.
  • Basic understanding about Data Science and Machine Learning.
  • Basic understanding of Pandas, Numpy and Matplotlib.

Description

ARE YOU LOOKING A FAST AND EASY WAY TO CREATE WEB APPS AND DASHBOARDS FOR YOUR DATA SCIENCE AND MACHINE LEARNING PROJECTS THEN THIS IS THE PERFECT COURSE FOR YOU.


Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science that can be used to share analytics results, build complex interactive experiences, and illustrate new machine learning models. In just a few minutes you can build and deploy powerful data apps.

On top of that, developing and deploying Streamlit apps is incredibly fast and flexible, often turning application development time from days into hours.


In this course you will learn:


  • Different input types in streamlit

  • Data display elements

  • Layouts and Containers

  • How to add images and videos to your Streamlit web app

  • Different Chart elements like Line Chart, Bar Chart etc...

  • 3 Complete Projects using Machine Learning and Streamlit.

  • Stock Market Index Prediction App

  • Calories Burned Calculator App

  • Insurance Premium Prediction App


At the end of the course, you will have built several applications that you can include in your Data Science and Machine Learning portfolio. You will also have a new skill to add to your resume.


After completing this course you will be able to quickly build web apps and dashboards for your Data Science and Machine Learning Projects using Streamlit.

Who this course is for:

  • Python Developers curious about Streamlit.
  • Data Scientists and ML Engineers who want to create a quick and beautiful user interface for their ML Models.
  • Anyone who wants to learn to build web apps in a fast and easy manner.

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