Streamlit
Welcome to our Streamlit course, a comprehensive material designed to empower you with the skills to create dynamic and interactive web applications using Streamlit. Whether you are a data scientist, machine learning engineer, or someone looking to showcase data-driven insights, this course will guide you through the process of building and deploying powerful data applications with ease.
DIFFICULTY LEVEL
Beginner to Intermediate
COURSE TYPE
Online
SCHEDULE
Self-paced
PRE-REQUISITES
Basic knowledge of Python recommended
TAGS
Streamlit, Data Visualization, Web Applications, Python, Interactive Widgets, Custom Components, Multimedia Integration
What you'll learn:
Introduction to Streamlit
Get an overview of Streamlit and understand how it can transform Python scripts into interactive web applications with minimal code.
Setting Up the Environment
Learn to set up Streamlit on Google Colab, install necessary libraries, and start your first Streamlit project.
Creating Basic Applications
Build your first Streamlit application, learn to display text, data, and visualizations, and explore the basics of Streamlit's syntax and structure.
Interactive
Widgets
Dive deep into creating interactive widgets like sliders, buttons, and text inputs to enhance user interaction in your applications.
Data Display
and Visualization
Learn to display and visualize data using Streamlit, integrating popular libraries like Matplotlib, Seaborn, and Plotly for dynamic visual content.
Advanced Features
and Custom Components
Explore advanced Streamlit features, including custom components, CSS styling, and JavaScript integration, Authentication, Session States, Access Control and more.
What you'll build in this course:
Interactive Widgets App
Create an application featuring sliders, buttons, text inputs, dropdowns, and radio buttons to capture user inputs dynamically.
Multimedia Integration App
Design an app that incorporates images, videos, and audio elements, making your applications more engaging and interactive.
Data Visualization Dashboard
Develop a dashboard to display and visualize data using various chart types, including line charts, bar charts, scatter plots, and heatmaps.
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Course Outline
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Frequently Asked Questions
What is Streamlit, and why should I use it?
Streamlit is an open-source Python library that allows you to create interactive, web-based applications easily. It is particularly popular among data scientists and machine learning engineers for its simplicity and ability to transform Python scripts into engaging applications without needing extensive web development knowledge.
Do I need prior experience with web development to take this course?
No prior web development experience is required. Streamlit abstracts the complexities of web development, allowing you to focus on building functionality using Python. Basic knowledge of Python is recommended to get the most out of this course.
What types of applications can I build with Streamlit?
You can build a wide range of applications with Streamlit, including data dashboards, machine learning model interfaces, data exploration tools, and multimedia-rich applications. The course includes projects that cover these use cases.
Can I deploy Streamlit applications to the cloud?
Yes, Streamlit applications can be deployed to the cloud using services like Heroku, AWS, or Streamlit’s own deployment platform, Streamlit Cloud. The course will guide you on how to deploy your applications online.
How do I make my Streamlit app interactive?
The course covers the creation of interactive widgets like sliders, buttons, text inputs, and more. These widgets allow users to interact with your application, making it more dynamic and responsive.
Streamlit Course
Description PDF
Download a copy of this course's description PDF!
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