Basics of Streamlit

🌟 Master Data Science & Machine Learning with Streamlit: Basics of Creating Web Applications with Pure Python! 🌟

Course Headline:

Create Web Applications for Your Data Science / Machine Learning Projects with Ease using Streamlit!

Course Description:

Dive into the world of web development without the complexities of HTML/CSS! As a fellow Data Science enthusiast, I've encountered the challenges of creating and deploying ML models on the web. But fear not, as Streamlit has revolutionized this process by allowing us to build professional-looking web applications using just Python. Join me in this journey where I share my insights and experiences to help you harness the power of Streamlit for your projects.

What You'll Learn:

• 📚 Streamlit Basics: Get familiar with the essentials of the Streamlit library, from adding text and data to creating interactive elements within your app.

  • Adding Text and Data
  • Plotting Graphs with Ease
  • Designing Layout for User Engagement
  • Enhancing Your App with Widgets
  • Personalizing Your Web Application's Theme
  • Building a Basic Web Application to Combine Streamlit and ML Models

• 🚀 Practical Application: By the end of this course, you will have the skills to create your own web app within a matter of hours, complete with a user interface for your ML models. Plus, you'll learn how to deploy your creation for the world to interact with!

Prerequisites:

• Ensure you have a grasp of Python fundamentals before jumping in.
• Embrace hands-on learning by coding along with the course material for optimal comprehension and skill acquisition.

This course is tailored for absolute beginners who are eager to understand how Streamlit can simplify their Data Science and Machine Learning projects. I've made every effort to present the content in a straightforward, accessible manner. You might notice that I don't adhere strictly to advanced coding practices initially; my aim is to keep things as simple as possible for your learning journey.

Tools & Environment:

• I recommend using Visual Studio Code (VS Code) for your coding tasks, but feel free to use whichever editor or environment you're most comfortable with!

Join me in this course and unlock the potential of Streamlit for your Data Science projects. Let's build something incredible together, step by step! 🤝

Course Outline:

1. Introduction to Streamlit: What is Streamlit and why is it a game-changer for Data Scientists?
2. Basic Components of Streamlit Apps: Learning the building blocks – text, data, graphs, layout, and widgets.
3. Styling Your Web Application: Making your app visually appealing through themes and customizations.
4. Integrating Machine Learning Models: How to seamlessly incorporate ML models into your Streamlit app.
5. Deployment Strategies: Options for deploying your Streamlit app for the world to see.
6. Real-World Projects: Applying your new skills to create impactful web applications that showcase your Data Science projects.

Ready to transform your Data Science projects into interactive web applications with just Python? Enroll in this course today and start building with Streamlit! 🖥️✨