A fast-track, project based course covering data science basics, ML, and visualizations.
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.
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..
Course Content
- Introduction –> 6 lectures • 14min.
- Extracting Basic Insights –> 3 lectures • 14min.
- Data Visualization –> 9 lectures • 50min.
- Machine Learning – Logistic Regression & Decision Tree Classifiers –> 10 lectures • 52min.
- Extra: Overfitting & Deploying the App –> 2 lectures • 6min.
Requirements
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 workflow:
- Data 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 Noticed
By 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.