Machine Learning Project as Web Apps

· September 8, 2021


Almost in all industries where Machine Learning is heavily utilized most of the individuals and companies develops a Machine Learning project. But that does not mean everything is done, there is one more step to make it useful. Making it accessible for everyone that is in target user scope by opening the project to the internet. In this situation, nowadays, Streamlit is a trending tool heavily used to construct illustrative web apps, without a requirement of any knowledge on web development in advance. It offers engineers to host their project on the server and make it available for use. Having begun to become a criteria in job applications, Streamlit is used by prestigious companies such as Google, Yelp & Uber. This course covers how to create an ML model and how to open your model for use by hosting it on the server.

Kick-starting with the concept “magic commands” which allow users to write markdown and data to an app, the course then introduces how to accomplish simple tasks such as displaying charts & media using Streamlit. In addition, interactive widgets & designing the sidebar will further be explained along with how to lay out an app. Finally, the course wraps up the concepts that have been explained by creating a final project on “custom trained model deployment and usage by the visitors/members”; which solidifies the knowledge of the newcomers to Streamlit.


  • Additional access to active mentoring by experts of the Global AI Hub 
  • A joint certificate issued by Global AI Hub for each successful learner  

Sponsored by       

  • Thanks to the Swiss-based AI Business School and the «10million.AI» project this course is free.
  • It is part of the national education campaigns aiming at educating more than 10 million learners for free on AI and other digital technologies.




  • Welcome to Machine Learning Project as Web Apps Course


  • Magic Commands
  • Display text
  • Display data
  • Display charts
  • Display media
  • Display interactive widgets
  • Control flow
  • Add widgets to sidebar
  • Lay out your app
  • Display code
  • Display progress bar and status
  • Placeholders, help, and options
  • Final Project: “Custom trained model deployment and usage by the visitors/members”


The course includes a series of lessons that lead you through the content in small, bite-sized learning blocks. Each lesson includes exciting video sessions followed by thought-provoking assessment questions.

  • Video sessions have to be marked as complete and can be accessed freely after the completion of each lesson
  • Assessment questions are graded for the calculation of certification progress
  • Each day has a “Materials” section to help you revise the topics that are seen that day
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