What you'll learn

Build interactive data dashboards with Python, using Streamlit, without needing web development expertise
Transform static data analyses (Pandas, NumPy) into engaging web applications that can be shared and explored by othersBI Professionals/Report Builders
Create custom data-driven tools and visualizations, using Streamlit components, to prototype ideas and explore datasets rapidly
Deploy interactive Streamlit apps to the cloud and share them with anyone, using free and easy-to-use hosting platforms
Integrate external data sources (CSV, JSON, APIs) into Streamlit apps to create dynamic and up-to-date visualizations
Design intuitive user interfaces for data exploration using Streamlit's layout options (columns, tabs, expanders)
Customize the appearance of Streamlit apps using themes and custom CSS to match branding or personal preferences

Requirements

Basic computer literacy. No prior programming experience is required. We'll cover all the necessary Python and Streamlit concepts from the ground up.

Description

Are you a data scientist, analyst, engineer, or researcher who works with Python? Do you want to share your data insights in a more engaging and interactive way, without having to learn complex web development frameworks? Then this course is for you!Streamlit is a revolutionary open-source Python library that makes it incredibly easy to build beautiful, interactive web applications for data science and machine learning. With Streamlit, you can turn your data scripts into shareable web apps in minutes, using only Python. No need for HTML, CSS, or jаvascript!This comprehensive course will guide you from the very basics of Streamlit to building and deploying sophisticated, interactive data dashboards and tools. You'll learn how to:Get Started: Set up your development environment and create your first Streamlit app.Display dаta: Work with text, tables, and a wide variety of charts (line charts, bar charts, area charts, and more) using Streamlit's built-in functions and popular libraries like Matplotlib and Plotly.Add Interactivity: Use Streamlit's powerful widgets (buttons, sliders, selectboxes, text inputs, etc.) to create dynamic applications that respond to user input.Control Layout: Organize your apps with columns, tabs, expanders, and containers for a clean and intuitive user interface.Work with dаta: Load data from CSV files, JSON files, and even external APIs.Persist State: Store user preferences and data across sessions using cookies.Deploy Your Apps: Share your creations with the world using Streamlit Sharing and other cloud deployment options.Go Beyond the Basics: Learn how to extend the capabilities of Streamlit by building custom components using React, opening up endless possibilities for creating unique and powerful data applications.This course emphasizes hands-on learning, with numerous examples, practical exercises, and skill challenges to reinforce the concepts. By the end, you'll be able to confidently build and deploy your own interactive data apps with Streamlit, transforming the way you work with and communicate data. Whether you're a seasoned data professional or just starting your journey, this course will empower you to create compelling data-driven web applications with ease. And if you're new to Python, don't fret! There is a full-length introduction to Python included as an Appendix which is included to get anyone up and running writing pythonic code in no time.See you inside!
Anyone interested in turning Python scripts into interactive web applications,Individuals with some Python experience who want to rapidly prototype data-driven applications and dashboards,Data professionals (analysts, scientists, engineers) who want to share their work interactively and create internal tools, without complex web development,Researchers, academics, and educators who want to create interactive visualizations and simulations to explain concepts or share findings effectively

Homepage:

https://www.udemy.com/course/master-streamlit-build-interactive-data-apps-with-python/