What will you learn in Building the Frontend of Python Web Applications with Streamlit Course
- Set up and configure Streamlit to build interactive Python web applications
- Use Streamlit widgets (sliders, buttons, text inputs) to capture user input dynamically
- Display data with tables, charts (Matplotlib, Altair), and maps for rich visualizations
- Organize layouts and themes using columns, containers, and custom CSS
- Manage application state, caching, and handle user-triggered callbacks
- Integrate external APIs, authentication, and deploy Streamlit apps to production
Program Overview
Module 1: Introduction to Streamlit & Setup
⏳ 1 day
Topics: Installing Streamlit, project structure, running the first app
Hands-on: Create and launch a “Hello, Streamlit!” app
Module 2: Widgets & User Input
⏳ 1 day
Topics: Input widgets (text inputs, sliders, checkboxes), form handling
Hands-on: Build a simple BMI calculator with interactive inputs
Module 3: Data Display & Visualization
⏳ 1 day
Topics: Displaying DataFrames, Matplotlib/Altair charts, map components
Hands-on: Render a COVID-19 time-series chart and interactive map
Module 4: Layouts, Themes & Styling
⏳ 1 day
Topics: Columns, expanders, tabs, custom themes, CSS injection
Hands-on: Design a two-column dashboard with dark and light theme toggles
Module 5: Media, Markdown & Interactivity
⏳ 1 day
Topics: Displaying images, audio/video, Markdown formatting, callbacks
Hands-on: Create an interactive image gallery with caption filters
Module 6: State Management & Caching
⏳ 1 day
Topics: Session state, caching data and functions for performance
Hands-on: Cache expensive API calls and preserve user selections across reruns
Module 7: Integrations & Authentication
⏳ 1 day
Topics: Consuming REST APIs, OAuth basics, embedding third-party content
Hands-on: Build a login-protected news reader app using a public API
Module 8: Deployment & Scaling
⏳ 1 day
Topics: Dockerizing Streamlit apps, Streamlit Cloud, CI/CD pipelines
Hands-on: Containerize your app and deploy to Streamlit Community Cloud
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Job Outlook
- Streamlit expertise is highly valued for roles like Data Scientist, BI Developer, and Python Web Developer
- Common industries include fintech, healthcare analytics, and SaaS startups leveraging rapid prototyping
- Salaries range from $80,000 to $130,000+ depending on experience and location
- Skills in building data-driven dashboards and deploying Python apps accelerate career growth in data-focused teams
Specification: Building the Frontend of Python Web Applications with Streamlit
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FAQs
- No prior frontend experience is required; basic Python knowledge is sufficient.
- The course introduces Streamlit and frontend concepts for Python web apps step by step.
- Beginners can follow along with hands-on exercises to create interactive web interfaces.
- Knowledge of HTML, CSS, or JavaScript can help but is not mandatory.
- By the end, learners can build functional, interactive frontends for Python applications.
- Yes, the course covers interactive elements like buttons, sliders, input boxes, and forms.
- Learners practice capturing user input and dynamically updating application content.
- Techniques for arranging layouts and widgets to enhance user experience are included.
- Hands-on projects demonstrate practical applications of these interactive components.
- Advanced UI customization may require additional exploration beyond the course.
- Yes, the course teaches integrating data visualization libraries like Matplotlib, Plotly, or Seaborn with Streamlit.
- Learners practice displaying charts, graphs, and tables interactively in web apps.
- Skills help build dashboards, reports, or analytical tools with real-time updates.
- Techniques include customizing visuals and updating them dynamically based on user input.
- Advanced visualization techniques may require additional study.
- Yes, the course introduces deployment concepts to make Streamlit apps accessible online.
- Learners practice hosting applications on platforms like Streamlit Cloud or other web servers.
- Guidance includes environment setup, dependencies management, and sharing URLs.
- Deploying projects helps showcase applications to potential users or employers.
- Advanced deployment strategies like CI/CD pipelines may require further learning.
- Yes, the course focuses on building functional frontends that interact with Python backends.
- Learners practice creating user interfaces that handle data input, processing, and output.
- Integration with Python scripts, APIs, or databases is demonstrated for real-world applications.
- Projects help learners understand full-stack workflows, even if backend work is minimal.
- Advanced full-stack features may require additional courses or experience.
