- Y4 S1: Machine learning 2 CW (Classification Network on the Iris Dataset): 92.5% https://github.com/HarryLyness/Machine-Learning-2-CW
- Y3 S2: Machine Learning CW (Stochastic-Optimisation-for-Matrix-Completion): 88% https://github.com/HarryLyness/ML1-Stochastic-Optimisation-for-Matrix-Completion
- Y3 S2: Numerical optimisation CW: Masters 90% https://github.com/HarryLyness/Numerical-Optimisation-
- Y3 S1: Numerical Solution to Evolutionary Equations CW: Masters (92%) https://github.com/HarryLyness/Numerical-Solution-to-Evolutionary-Equations-Coursework
- Y1 S2: Permutation Cipher (80%): https://github.com/HarryLyness/Permutation-Cipher-2021-
- Y4 S2: Time Series CW: 92% https://github.com/HarryLyness/Time-series-coursework
- Y4 S2: Optimizing Public Policy Planning using Data Analysis (Applied Data Science CW1): 80% https://github.com/HarryLyness/Optimizing-Public-Policy-Planning-using-Data-Analysis
- Y4 S1: Applied Statistical Inference CW: Masters 83% https://github.com/HarryLyness/Applied-Statistical-Inference
- Y3 S1: Analysing Literature, Pollution and Crime Data (Data Science CW2) (84%): https://github.com/HarryLyness/Data-Science-Coursework-2
- Y3 S1: Analysing Orchids, Hospital and Ambulance Data (Data Science CW1) (76%): https://github.com/HarryLyness/Data-Science-Coursework-1
- Y3 S2: Parallel Nonlinear thermal Conduction: Masters, 83% https://github.com/HarryLyness/MPI-FORTRAN-90-Nonlinear-Thermal-Conduction
- Y3 S2: Nonlinear-Thermal-Conduction (Scientific Computing): Masters, 92%, 2nd/20, https://github.com/HarryLyness/-Nonlinear-Thermal-Conduction-Quasi--Newton-Methods
- (Y2-Y3) Summer 2022: Mini project which involved using Linear Modelling to show that Friends is a remarkable TV Show\Sitcom. NOTE: Completed after taking Statistics 2B and reading 'Linear Models with R - Julian J.Faraway'. https://github.com/HarryLyness/Linear-Modelling-Friends-Sitcom
