A collection of Python projects built from scratch — from beginner fundamentals to real-world applications — as a structured path into Machine Learning.
Learned Python with Claude & ☕ — one project at a time.
This repository is my complete Python learning log. Every project here was built hands-on to deeply understand a specific concept — not just read about it.
It covers everything from core Python (OOP, file handling, error handling) to data science libraries (NumPy, Pandas, Matplotlib), ending with real-world capstone projects. Beginner programs all the way to production-style code — all in one place.
Core Python → NumPy → Pandas → Matplotlib → Capstone
Fundamentals-heavy projects covering OOP, modules, file I/O, and error handling.
Array operations, broadcasting, statistical analysis, and vectorised computation.
DataFrames, data cleaning, groupby, merging, and real CSV workflows.
Charts, subplots, annotations, and building visual dashboards from data.
Full end-to-end projects solving real problems — combining everything above.
- Language — Python 3
- Libraries — NumPy, Pandas, Matplotlib
- Tools — VS Code, Claude, Git
Complete this roadmap → enter Machine Learning with a strong Python foundation.
Built project by project, concept by concept — with Claude and way too much coffee ☕