Advanced Level
Four A*s. One compressed year. No dilution.
People said A-Levels were hard enough to need two years. I took that as a scheduling suggestion and gave them one: Mathematics, Further Mathematics, Physics and Computer Science, with both stages sat together.
General Certificate of Education
Advanced Level Grade ReportComputer Science
Syllabus 9618 // Advanced Systems & TheoryFurther Mathematics
Syllabus 9231 // Advanced Calculus & Complex AlgebraMathematics
Syllabus 9709 // Pure Math, Mechanics & StatsPhysics
Syllabus 9702 // Fields, Waves & Particle PhysicsWhat this year proved.
The grades mattered, but the more useful proof was endurance: learning difficult material quickly, holding pressure for months, and switching between four subjects that punish completely different kinds of sloppy thinking.
99th percentile - Cambridge A-Levels
Request Certificates
Cambridge Outstanding Learner Awards
Formal recognition from Cambridge International Examinations for high academic performance nationally.
Best Across Cambridge A-Levels
Highest total score achieved nationally across all Cambridge A-Levels.
Computer Science
Top in Country
Ranked #1 in the country for Advanced Level Computer Science.
Highest Grade Based Award
Awarded for securing 4 A* grades or more in a single exam series.
Highest Level of Achievement
Outstanding award for academic excellence.
Highest Level of Achievement
Outstanding award for academic excellence.
Highest Level of Achievement
Outstanding award for academic excellence.
Four Core Disciplines
A detailed breakdown of the components and lessonwise topics studied under each advanced level subject.
Computer Science was where abstract logic became machinery. I learned algorithms, data structures, architecture, databases, networking, security, and enough programming to appreciate how quickly “simple” requirements become complicated systems. Debugging was probably the best teacher. A program does not care how convincing your explanation is; it either survives the input or it does not. The course trained me to move between theory and implementation, to trace failures patiently, and to design with the machine rather than around it. Achieving the highest grade mattered, but understanding why systems behave the way they do mattered more.
Covers fundamental computing principles, including algorithms, data representation, system architecture, and software concepts. Develops understanding of computational logic and theoretical problem-solving.
Focuses on coding, problem-solving, and algorithm implementation in a high-level language and Pseudocode. Develops debugging, testing, and structured programming skills. Applies theoretical knowledge practically, creating working software solutions.
Expands into advanced computing topics, including system design, software engineering, algorithms, and data structures. Develops ability to solve complex problems and design efficient computational solutions.
Applies programming knowledge to develop real-world software projects. Emphasizes debugging, testing, optimization, and project management skills. Develops proficiency in translating requirements into code, problem-solving in practical contexts, and delivering functional software solutions.
Further Mathematics was the subject that made difficulty enjoyable. Complex numbers, matrices, differential equations, advanced calculus, mechanics, and statistics kept forcing me to abandon the first obvious method and look for structure instead. I liked that. The subject rewards patience, abstraction, and the willingness to sit with a problem long enough for several separate ideas to suddenly connect. It also made standard Mathematics feel much less intimidating. The A* mattered, but the lasting result was learning to stay calm when a page initially looked like it had been designed by an enemy.
Explores complex numbers, matrices, and advanced algebraic techniques. Develops the ability to work with abstract mathematical concepts and multi-step problem-solving. Emphasizes logical reasoning and precision.
Covers hyperbolic functions, differential equations, Maclaurin and Taylor series, and polar coordinates. Enhances understanding of continuous systems and provides a foundation for advanced mathematical modeling.
Applies advanced mathematical methods to complex mechanics problems, including motion, forces, and equilibrium. Develops systematic problem-solving strategies and the ability to model realistic scenarios.
Explores probability distributions, hypothesis testing, and statistical modeling. Develops the ability to analyze data, draw conclusions, and assess statistical reliability.
Mathematics gave me the language I use everywhere else. Calculus, algebra, probability, statistics, modelling, and functions were not isolated chapters for long; they became ways of describing change, uncertainty, structure, and relationships. I learned to move from a messy question to a clean model, test whether the model deserved trust, and communicate the reasoning without hiding behind notation. The A* was the result on paper. The more useful outcome was becoming comfortable with precision and with asking why an answer must be true.
Covers quadratics, functions, coordinate geometry, circular measure, trigonometry, and series. Emphasizes algebraic manipulation, function analysis, and geometric reasoning. Develops foundational skills in differentiation and integration, essential for advanced mathematical problem-solving.
Delves into advanced calculus, including differentiation and integration techniques. Explores trigonometric identities, sequences, and series. Enhances mathematical reasoning and problem-solving abilities through complex functions and their applications.
Focuses on forces, motion, Newton's laws, kinematics, and vectors. Applies mathematical principles to model physical phenomena, fostering an understanding of dynamics and equilibrium in various contexts.
Introduces probability, data analysis, distributions, and statistical inference. Develops skills in summarizing data, calculating probabilities, and modeling real-world situations using statistical techniques.
Physics was where the mathematics stopped sitting still. Mechanics, waves, electricity, magnetism, fields, quantum ideas, and practical experiments turned equations into explanations for actual behaviour. I liked the tension between ideal models and imperfect measurements, because reality always adds one more variable than the textbook promised. Practical work made error, assumptions, uncertainty, and measurement impossible to ignore. The course also trained me to move between diagrams, equations, experiments, and physical intuition without treating any one of them as sufficient on its own. The A* mattered, but the lasting lesson was more useful: model carefully, measure honestly, question the assumptions, and revise when the world disagrees.
Tests core concepts through multiple-choice questions covering mechanics, waves, electricity, and energy. Develops speed, accuracy, and conceptual clarity under timed conditions.
Focuses on fundamental physics principles including mechanics, electricity, waves, and thermal physics. Develops structured problem-solving skills and the ability to apply theory to numerical calculations.
Emphasizes experimental design, data collection, error analysis, and practical problem-solving. Develops skills in precise measurement, systematic recording, and critical evaluation of results.
Expands on AS topics with deeper theory, including mechanics, electricity, magnetism, and modern physics. Focuses on complex problem-solving, derivation of formulas, and application to advanced scenarios.
Combines practical investigation with assessment of experimental techniques, data reliability, and project analysis. Requires planning, execution, and evaluation of experiments. Develops transferable skills in scientific methodology & evaluation.
Built During That Year
Simulations I made during my A-Levels, one per subject, because reading about an idea and making it run are different things. Have a go.
Both algorithms find the shortest route. Dijkstra searches evenly in every direction. A* adds an estimate of the distance left, so it stops exploring where the goal clearly isn't.
Same walls, same length of route. Try leaving the grid empty, then box the goal in: the gap between them changes.
In polar coordinates a single number decides the whole shape. Set k = p/q and watch the pen: the petal count and where the curve finally closes both follow from whether p and q are odd.
A differential equation doesn't give one answer. It gives a whole family of them, and the constant of integration picks one member. Click a point: you just chose the constant.
An electron can only sit on fixed energy levels, so when it falls it can only release fixed amounts of energy. Each amount is one exact colour. That is the whole of a line spectrum.
Find all four visible lines of hydrogen. Hint: they all end on the same level.
What It Built
That year taught me how to move quickly without becoming careless, go deep without disappearing into one topic, and keep several demanding systems running at the same time.