Building the Frontend of Python Web Applications with Streamlit Course Syllabus

Overview: This course provides a hands-on introduction to building interactive, data-driven web applications using Streamlit, a powerful Python library for frontend development. Over approximately 8 days of project-based learning, you'll progress from setting up your environment to deploying scalable apps. Each module combines concise theory with live coding exercises, emphasizing real-world use cases in data visualization, user input handling, and state management. By the end, you’ll deploy a production-ready app using Docker and Streamlit Community Cloud, gaining practical skills ideal for data scientists, analysts, and Python developers.

Module 1: Introduction to Streamlit & Setup

Estimated time: 3 hours

• Installing Streamlit and setting up the development environment
• Understanding Streamlit app structure and execution model
• Running and debugging the first Streamlit application
• Creating a 'Hello, Streamlit!' app with basic output

Module 2: Widgets & User Input

Estimated time: 3 hours

• Using input widgets: text inputs, sliders, checkboxes, and select boxes
• Handling user input dynamically in real time
• Grouping inputs with forms and disabling submission states
• Building a BMI calculator with interactive inputs and feedback

Module 3: Data Display & Visualization

Estimated time: 3 hours

• Displaying Pandas DataFrames with dynamic filtering
• Integrating Matplotlib and Altair for interactive charts
• Plotting geospatial data using Streamlit map components
• Creating a time-series dashboard for COVID-19 data

Module 4: Layouts, Themes & Styling

Estimated time: 3 hours

• Organizing content with columns, containers, and expanders
• Using tabs for multi-section layouts
• Customizing themes and toggling dark/light modes
• Injecting custom CSS for branding and layout control

Module 5: Media, Markdown & Interactivity

Estimated time: 3 hours

• Displaying images, audio, and video files
• Formatting text with Markdown for rich content
• Implementing callbacks and event-driven updates
• Building an interactive image gallery with caption filters

Module 6: State Management & Caching

Estimated time: 3 hours

• Managing session state to preserve user inputs
• Caching functions and data loading for performance
• Handling user-triggered callbacks efficiently
• Optimizing app reruns and reducing latency

Module 7: Integrations & Authentication

Estimated time: 3 hours

• Consuming REST APIs within Streamlit apps
• Implementing basic authentication with OAuth
• Embedding third-party content securely
• Building a login-protected news reader using a public API

Module 8: Deployment & Scaling

Estimated time: 4 hours

• Containerizing Streamlit apps with Docker
• Deploying to Streamlit Community Cloud
• Setting up CI/CD pipelines for automated updates
• Best practices for scaling and monitoring production apps

Prerequisites

• Familiarity with Python programming (variables, functions, conditionals)
• Basic knowledge of Pandas for data manipulation
• Understanding of HTTP and REST APIs (helpful but not required)

What You'll Be Able to Do After

• Build interactive, data-driven web applications using only Python
• Design responsive layouts with widgets, charts, and media
• Manage application state and optimize performance with caching
• Integrate external data sources and secure user access
• Deploy production-ready Streamlit apps using Docker and CI/CD