Artificial Intelligence and Computer Science BSc (Hons) personal statement example

Why do you want to study this course or subject?

On an orienteering course the quickest line between two controls is rarely the straight one. I have spent many Sunday mornings deciding whether to climb a ridge or follow the path around it. When I met Dijkstra's algorithm in A-level Computer Science, I recognised the same trade-off written down precisely: every option given a cost, and a method guaranteed to find the cheapest route. I am drawn to computer science by the idea that a problem I solved by instinct could be stated clearly enough for a machine to solve reliably. Artificial intelligence takes this further, because many real problems are too large to search exhaustively. In the early chapters of Russell and Norvig's Artificial Intelligence: A Modern Approach, I was struck by how A* search uses a heuristic to avoid exploring hopeless routes. I was also struck by the care needed to show that a heuristic never overestimates the true cost. Melanie Mitchell's Artificial Intelligence: A Guide for Thinking Humans gave me a useful counterweight. She shows how systems that perform impressively can fail on inputs a person would find trivial. I want to study both the rigorous foundations of computing and the harder question of how to build systems that behave sensibly beyond the examples they were designed around.

How have your qualifications and studies helped you to prepare?

My A-level subjects support each other more than I expected. Graph theory in Further Maths gave me the language for the search problems I enjoy. Matrices made sense of the transformations behind graphics and, later, the weighted sums inside simple neural networks. Physics has trained me to check whether an answer is reasonable before trusting it. For my Computer Science NEA I am building a scheduler that allocates lunchtime clubs to rooms and staff without clashes. I treated it as a constraint satisfaction problem. My first version used plain backtracking and slowed badly once I added realistic data. Adding forward checking, and choosing the most constrained club first, made it fast enough to use. Writing up why those changes worked helped me understand the algorithm far better than coding it had. Outside the syllabus, I wrote a Connect Four program in Python using minimax with alpha-beta pruning. I wrote my own evaluation function, which scored open lines of three, and tested versions against each other over hundreds of games. Watching a deeper search beat a cleverer evaluation showed me how much both matter. I now want to see whether a small learned evaluation could compete with the one I designed by hand.

What else have you done to prepare outside of education, and why are these experiences useful?

For the past eighteen months I have worked Saturdays at a garden centre. I work the tills, rotate stock and water the plant tables before opening. Customers often ask why a plant is failing. I have learned to ask about light and watering before suggesting anything. It is a small habit of gathering evidence first that also helps when I debug code. My manager now trusts me to cash up and to show new weekend staff how the till system handles returns. On Tuesday evenings I take my younger brother to his swimming club. I usually do Further Maths problems on the viewing balcony, which has made me good at working in short, focused stretches. Orienteering remains my main hobby. I compete in local events and, for the last year, have helped the club put out controls for junior courses. Planning a junior course is its own puzzle: legs must be short and safe but still involve a real choice of route. I also help at my school's Year 9 programming club. Explaining loops and lists to younger students has shown me how often confusion comes from one unstated assumption, and I enjoy finding it. These commitments have taught me to manage my time and to communicate clearly. They have also kept me curious about how people and systems make decisions.