Building Data Apps with Python and Streamlit

Data is only as valuable as the insights you can share. If you want to present your data analysis, machine learning models, or data science workflows as interactive web applications without learning complex web development frameworks, this course is your perfect starting point. You will transform from a Python coder into a creator of functional, shareable data applications. Through structured written lessons, you will learn to build, test, and deploy interactive tools step-by-step. What you'll learn: Understand core Streamlit concepts like reactive state, caching, and data flow; Build interactive user interfaces with sliders, dropdowns, and text inputs; Display dynamic dataframes, charts, and plots directly in your application; Integrate modern data libraries to process and visualize datasets on the fly; Manage application state to handle multi-step user workflows; Deploy your completed data applications to the cloud for public or private sharing. We begin with foundational definitions, installation guides, and basic layout structures before moving on to practical interface components and deployment strategies. This text-based course is designed for beginners, data analysts, and Python enthusiasts who want to showcase their work, requiring only basic Python knowledge and no prior web development experience. Start building and sharing your own interactive data tools today.