Build a Diabetes Dashboard with Python, Streamlit & ML

A fast-track, project based course covering data science basics, ML, and visualizations.
What you'll learn
Build an interactive Streamlit dashboard app in Python from scratch, using real-world diabetes data.
Create insightful data visualizations with Pandas, Matplotlib, and Seaborn to explore health datasets.
Develop and integrate machine learning models (e.g., logistic regression, decision tree) into a deployable web app for diabetes prediction.
Deploy a polished, user-friendly data science project that demonstrates both coding and applied ML skills - perfect for portfolios or job applications.
Requirements
A computer (Windows, Mac, or Linux) with internet access.
Basic familiarity with Python (variables, functions, simple scripts) is helpful but not required - I'll guide you step by step.
Willingness to install Anaconda (free, beginner-friendly Python distribution) - I'll walk you through the setup process in detail.
No prior experience with data visualisation, machine learning, or Streamlit is needed - we'll build everything from scratch.
Description
Are you ready to fast-track your data science journey and build real projects you can proudly showcase? This course is your direct path to becoming a practical, project-oriented data scientist. We've eliminated the endless theory and created a curriculum that gets you hands-on from Day 1. Instead of spending weeks stuck in dry concepts, you'll learn by doing-working through a complete, project-based curriculum that takes you from raw data all the way to a polished, interactive application.We'll use the Pima Indians Diabetes Dataset as our guide, a classic challenge that provides the perfect opportunity to master a full, end-to-end data science workflowata exploration & cleaning - Learn how to quickly uncover insights in real-world datasets.Data visualization - Transform numbers into clear, meaningful charts and graphs.Machine learning models - Train and evaluate predictive models step-by-step.Streamlit web apps - Bring your work to life with shareable, interactive dashboards.A Portfolio Piece That Gets You NoticedBy the end of this course, you won't just "know the concepts"-you'll have a fully functional data science project to add to your resume, GitHub, or LinkedIn. This isn't just about earning a certificate; it's about building a portfolio that proves you have the skills to solve real-world problems. You'll be able to confidently discuss your work, share your code, and showcase a finished product that demonstrates your ability to navigate the entire data science lifecycle. Whether you're a student, a career-changer, or a busy professional, this fast-track approach ensures you skip the fluff and focus on what really matters: building a skillset through projects.This course is fast to learn, practical to apply, and built for real results. Stop dreaming about a career in data science and start building your future.
Who this course is for
Beginner Python developers curious about Data Science
Students interested in conducting medicine/STEM research using ML
Students wanting to learn how to develop an app with Python through Streamlit
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