Computer Science Personal Statementfor Oxford, Cambridge & Imperial

Outside lessons, I built a command-line task manager in Python to practise structuring a program around clear abstractions rather than writing everything in one block. I used dictionaries to store tasks with priorities and deadlines, implemented file-based persistence with JSON, and added sorting and filtering. The most useful part was refactoring. My first version worked but was difficult to extend because I had tangled the storage logic with the display logic. Separating them into distinct functions made the program easier to test and showed me why abstraction matters practically, not just as a concept in a textbook. I also worked through several chapters of Nand2Tetris, which changed how I understood computers. Building logic gates, then an ALU, then a simple CPU from first principles made the layers between hardware and software feel concrete rather than mysterious. What stayed with me was how each abstraction hides complexity in a way that makes the next layer possible. That idea now shapes how I think about software design as well. Tutoring younger students in mathematics has reinforced the same discipline. Explaining a method clearly forces me to identify where my own reasoning relies on assumption rather than logic. That habit of checking whether I can justify each step, not just get the right output, is what I want to develop further through a Computer Science degree.