- Reading time: 3 minutes
- Price: Free download
- Published: 5th October 2026
- Word count: 646 words
- File format: Text
Why do you want to study this course or subject?
At the hardware shop where I work on Saturdays, I cut house keys on a duplicating machine. Most cylinder keys share a small set of cut depths, so a key is really a short sequence of numbers. One quiet afternoon I worked out how many distinct keys a five-pin lock could allow, then wondered which combinations a manufacturer would avoid and why. That habit of turning something physical into something countable, then asking whether a program could check my reasoning, is why I want to study computer science and mathematics together. I enjoy the point where they meet. In mathematics I like proof, because an argument either holds for every case or it does not. In programming I like seeing a design built on that argument actually run. Reading Pólya's How to Solve It changed how I work: his advice to try a simpler related problem first is now my first move when stuck, whether on an induction proof or a recursive function. I want a degree where algorithms are treated as mathematical objects whose correctness and efficiency can be proved, not only tested, and where I can explore discrete mathematics, logic and complexity, which I have only glimpsed at school.
How have your qualifications and studies helped you to prepare?
I take Maths, Further Maths, Computer Science and Economics at A level. Further Maths introduced me to proof by induction and to graph algorithms; tracing Dijkstra's algorithm by hand made me curious why it fails with negative edge weights, which led me to read about the Bellman-Ford algorithm. For my Computer Science NEA I am writing a Python program that generates nonogram puzzles and checks that each has exactly one solution. My first solver used plain backtracking and took minutes on a 15 by 15 grid. I added line-by-line deduction, filling any cell that every valid arrangement of a row agrees on, before falling back to search, and the same grids now solve in under a second. Writing up why the deduction step can never remove a valid solution was the closest I have come to proving something about my own code. Economics has been more useful than I expected: building simple supply and demand models in a spreadsheet taught me to state assumptions clearly and to notice when an output depends on one uncertain number. The faster solver also left me thinking about the difference between performance on my chosen grids and a general claim about efficiency. I want to learn how to describe that distinction mathematically.
What else have you done to prepare outside of education, and why are these experiences useful?
Besides cutting keys, my job involves mixing paint to a formula, working the till and helping customers find the right parts, and it has made me comfortable explaining technical things to people who just want their problem solved. Once a week I help at a lunchtime maths club for Year 8 students. Explaining negative numbers to a boy who knew the rules but could not say why they worked made me find three different ways into the same idea, and I now notice how often something I think is obvious rests on a step I skipped. With a friend from my Computer Science class I built a small web scoreboard for our house quiz. She designed the interface; I wrote the scoring logic and a script to import answers from a shared form. We agreed the data format before writing anything, so our halves fitted together first time, and the scoreboard ran for all six rounds without a fix mid-event. Outside school I orienteer with a local club, mostly on junior courses. Choosing between a longer path and a shorter climb while tired is a route problem with imperfect information, though mostly I just enjoy being outdoors on a Sunday morning.