Academic e-portfolio

MSc Data Science

Learning artefacts, assignments, visualisation and machine learning work, research and reflections from the MSc Data Science at the University of Essex, completed in 2026 alongside a decade of banking technology practice.

MSc Data Science — University of Essex

University of Essex · July 2024 cohort to January 2026 cohort

Completed Seven modules completed

Deciphering Big Data

Full e-portfolio

Machine Learning

Full e-portfolio

Research Methods

Full e-portfolio

Big Data Reflection

Module reflection

Completed modules

Seven modules, July 2024 to January 2026

Listed in cohort order. Modules with a published e-portfolio or reflection link to it; the others are documented here only.

Module 01 · July 2024 cohortCompleted

Visualising Data

Grammar and idioms of visualisation

Learning outcomes

  • Apply visualisation grammar across the full process
  • Evaluate tools for exploring complex data
  • Communicate insights for decision-making
  • Plotly
  • Seaborn
  • Storytelling
Module 02 · October 2024 cohortCompleted

The Data Professional

Roles, ethics and tools of the data professional

Learning outcomes

  • Identify roles considering ethics, law and privacy
  • Develop GitHub and workflow automation skills
  • Analyse data-to-knowledge transformation
  • Git / GitHub
  • Ethics
  • CI/CD
Module 03 · January 2025 cohortCompleted

Numerical Analysis

Mathematics and statistics for data science and AI

Learning outcomes

  • Mathematical and statistical concepts for data science and AI
  • Apply methods in data-driven decision-making
  • Critically evaluate statistical analyses
  • Numeracy
  • R Programming
  • Statistics
Module 04 · April 2025 cohortCompleted

Deciphering Big Data

Big data technologies, management and compliance

Learning outcomes

  • Understand the 4 Vs and common data formats
  • Build ETL pipelines with Python and SQL
  • Apply GDPR and data governance principles
  • Python
  • SQL
  • MongoDB
  • GDPR

Reflection

This module sharpened my technical skills in data cleaning, modelling and governance. I now build pipelines with privacy-by-design thinking.

E-portfolio Reflection
Module 05 · July 2025 cohortCompleted

Machine Learning

CNNs, transfer learning, Industry 4.0 and 5.0

Learning outcomes

  • Implement neural networks for image classification
  • Apply transfer learning with pre-trained models
  • Understand explainability (SHAP, Grad-CAM)
  • TensorFlow
  • Keras
  • CNN
  • XAI

Highlight

CIFAR-10 image classification with MobileNetV2 transfer learning reached 94.46% test accuracy, with Grad-CAM used to inspect what the model attends to.

E-portfolio Reflection
Module 06 · October 2025 cohortCompleted

Research Methods and Professional Practice

Scientific investigation, ethics, literature review and statistical analysis

Learning outcomes

  • Formulate research questions and hypotheses
  • Conduct systematic literature reviews
  • Prepare a dissertation proposal
  • Research
  • Academic Writing
  • Literature Review

Reflection

Explored qualitative, quantitative and mixed-methods approaches while completing statistical analyses and a research proposal for my workplace, evaluated through Rolfe et al.'s (2001) reflective framework.

E-portfolio Reflection
Module 07 · January 2026 cohortCompleted

MSc Computing Project

Independent final project, the capstone of the MSc

Learning outcomes

  • Plan and execute an independent, research-driven computing project
  • Apply data science and machine learning end to end on a real problem
  • Produce a dissertation with rigorous methodology, analysis and evaluation
  • Defend findings and reflect on professional and ethical implications
  • Capstone
  • Dissertation
  • Applied ML
  • Independent Research

Completed 2026

The capstone brought statistics, visualisation, big data, machine learning and research methods together in one dissertation-grade piece of work, completing the programme.