This repository documents my progression from Python fundamentals to machine learning and research-level programming.
The focus is not speed or shortcuts, but depth, clarity, and correctness.
01-Syntax-Mastery/
- Core Python syntax
- Control flow, data types, functions
- Clean, readable, predictable code
02-Computational-Physics/
- Physics-based programs
- Kinematics, dynamics, numerical simulations
03-Mathematical-Foundations/
- Algebra, calculus, linear algebra implemented in code
04-Logic-Algorithms/
- Algorithmic thinking
- Data structures and problem decomposition
05-Research-Projects/
- Larger systems
- Experimentation, analysis, and documentation
- No copy-paste learning
- No blind library usage
- Every program must be explainable line-by-line
- Progress is incremental and permanent
Status: Active