Build real-world projects: pipelines, dashboards, and ML applications
Build a reusable pipeline that ingests messy CSV data, handles missing values, normalizes columns, and outputs clean DataFrames.
Analyze sales data, compute KPIs, and build visualizations that tell the story — a complete reporting project.
Track expenses, categorize spending, and visualize where the money goes. A practical Pandas project you can actually use.
Parse server logs with regex, extract error patterns, and generate summary reports. Real-world file processing in Python.
End-to-end data science: clean data, engineer features, train a classifier, and predict which customers might leave.
Build a CRUD inventory system backed by SQLite. Classes, database queries, and a command-line interface all in one project.
Detect trends, seasonality, and anomalies in time-series business data using Pandas and Matplotlib.
Extract data from multiple sources, transform it with Pandas, and load it into a clean output — a beginner-friendly ETL project.