Portfolio
Projects & Modules
Research, commercial and academic work, strongest first — then 18 taught modules across an MSc in Data Science (University of Essex Online) and a BSc (Hons) Data Science (The Open University). Each module card opens that module's own page: its learning outcomes, reflection and the artefacts produced for it.
Strongest first
Selected projects
Research, commercial and academic work the supplied site evidences, ordered with the highest-value work first.
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Research · multimodal AI
Essex MSc Data Science Thesis
A multimodal driver behaviour evaluation system that combines telematics data, vision-language models and large language models to support richer behavioural assessment.
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Academic · this site
UoEOMScDataScience e-portfolio
The University of Essex Online MSc e-portfolio: MSc work, previous Honours material, academic reflections and published articles. This site is the rebuilt, recruiter-facing presentation of it.
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Commercial · client website
Pringle Padel
A company website developed for Pringle Padel, presenting the business, its services and its brand through a responsive web interface.
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Commercial · client website
The Bowyer Collective
A photography portfolio website developed for Chloe's Photography, designed to showcase visual work and provide a professional online presence.
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Commercial · client website
Chloe's Travelling Tutors
A business website created for Chloe's Travelling Tutors, presenting its tutoring services and providing a clear interface for prospective clients.
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Commercial · data engineering
Padel Scraper
A Python-based web scraping system that automatically collects padel results across divisions and transforms the extracted information into structured JSON.
Private commercial repository — not publicly linkable. No public link is published, so there is no dead link here.
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Personal · software engineering
Industry Zero
A private game-development project built in C#. The project provides a practical environment for exploring software architecture, game systems and interactive application development.
Private development repository — not publicly linkable. No public link is published, so there is no dead link here.
Programme pages
Academic
Programmes
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MSc Data Science
My MSc in Data Science with the University of Essex Online: reflective e-portfolios from each module, the research and literature review work behind them, and my MSc Computing Project.
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BSc (Hons) Data Science
The twelve 30-credit modules of my BSc (Hons) Data Science with The Open University, and the foundations they gave me in statistics, mathematics, computing and machine learning.
Open programme →
Body of work
Modules
Ordered by programme, then alphabetically. MSc Data Science modules first, then the BSc (Hons) Data Science foundation.
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Deciphering Big Data
The Deciphering Big Data module introduces the underpinning concepts and skills of data wrangling, with an emphasis on big data.
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Machine Learning
The Machine Learning module introduces machine learning with a practical approach, providing hands-on cases of real-world data analytics.
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Numerical Analysis
The Numerical Analysis module introduces key aspects of mathematics and statistics for data science and artificial intelligence.
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Research Methods and Professional Practice
The Research Methods and Professional Practice module provides a practical foundation in research methods that enables research in practical settings.
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The Data Professional
The Data Professional module explores and investigates the critical theoretical concepts in the discipline of data science, starting from data collection and then gradually leading to the stage where data is transformed into knowledge to…
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Visualising Data
The Visualising Data module introduces the underpinning concepts for processing and analysing datasets. It also provides data visualisation and presentation skills essential for a data scientist while improving decision making using data.
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Algorithms, data structure and computability
This module aimed to help me become a computational problem solver. I learned techniques to solve computational problems efficiently and applied those techniques using Python…
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Analysing data
This module explored fundamental statistical techniques and ideas for analyzing and interpreting data. It covered models for data, estimation, confidence intervals, hypothesis testing, and regression…
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Applied statistical modelling
What did wage rates depend on? How many medals was a nation predicted to win at the next Olympics? Could we predict a student’s exam score based on their age and which qualification they were studying…
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Data Management and analysis
This module addressed some of the key concepts required for the traditionally important area of data management and the increasingly important area of data analytics…
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Essential mathematics
This introductory module provided a broad and enjoyable foundation for university-level mathematics but required some prior knowledge…
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Interactive design and user experience
From small apps to large business systems, smartphones to intelligent environments, wearables to ambient installations, and virtual reality to augmented reality – interactive computing technologies had become part of the fabric of everyday…
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Introduction to computers and technology 1
This module was the first of two introducing computing and information technology concepts, such as digital technologies, programming, and networking…
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Introduction to computers and technology 2
This module built on Introduction to Computing and Information Technology 1 (TM111) and prepared me for further study of computing and IT modules…
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Introduction to statistics
This module taught me how to use basic statistical tools and quantitative methods useful in business, government, industry, medicine, the economy, and most academic subjects…
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Machine Learning and Artificial Intelligence
Intelligent assistants like Alexa and Siri, image searches that found the topic of a photo, and self-driving cars – these intelligent systems used machine learning to develop their expertise…
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Mathematical methods
This module taught mathematical methods used in modelling through their application to solving real-world problems. These methods include differential equations, linear algebra and vector calculus…
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Practical modern statistics
This module introduced four major topics of modern applied statistics: medical statistics, time series, multivariate analysis, and Bayesian statistics…
Open module →
Artefacts
The reports, literature reviews, presentations and worksheets produced across these modules are collected on the Evidence surface.