Software, Automation & Data
Specializing in Software, Automation, and Statistical Analysis with Python, Java, JavaScript, and R
About Me
My Computer Science studies at the Open University have covered software development, automation and data analysis. This portfolio brings together practical projects and statistical demonstrations, with source code where available.
I work primarily with Python, Java, and JavaScript, with additional experience in R for statistical analysis. I bring 7+ years of client-facing experience to technical projects, emphasizing problem-solving, agile workflows, and user-centric delivery. I’m seeking opportunities in software development or automation engineering.
Projects
Synthetic Time-Series Forecasting
A Python teaching demonstration using synthetic COVID-shaped counts. Includes an ARIMA forecast and held-out error measurements. These are simulated observations, not real COVID-19 data.
Project Files:
Global CO₂ Analysis
Interactive Plotly charts of emissions over time, country rankings and per-capita emissions, using Our World in Data.
View source code and project documentationSynthetic Economic Regression
An R demonstration of correlation and linear regression using 200 synthetic inflation and unemployment observations. The data are generated locally; the results do not establish real economic relationships.
Project Files:
Real-Time Crypto Trading Bot
JavaScript app using WebSockets to stream live Binance market data and compute RSI-based buy/sell signals. UI for price charts, holdings, and trade history.
Source code and live demo are not published in this repository.
Pong Game (Pygame)
Classic Pong game built with Pygame. Collision detection, score tracking, input handling. OOP structure for maintainability.
Source code and live demo are not published in this repository.
OOP Calculator (Java)
Functional calculator in Java applying encapsulation and inheritance. Clean structure for future features and UI improvements.
Source code and live demo are not published in this repository.
Reproduce the Demonstrations
All statistical examples on this page use synthetic data. Read the current summary for the methods, data generation and limitations.
- Setup instructions and source repository
- Current project summary (Markdown)
- Runnable Python demonstrations
- Runnable R regression demonstration
- Synthetic forecast metrics and NumPy statistics (JSON)
Descriptive Statistics with Python/NumPy
A seeded synthetic sample of 1,000 observations, with population standard deviation and quartiles computed in NumPy.
Skills & Technologies
Programming
- • Python
- • Java
- • JavaScript
- • R
- • HTML/CSS
Frameworks & APIs
- • Pygame
- • Node.js
- • React (learning/working knowledge)
- • RESTful APIs
- • WebSocket / Binance API
Tools & Concepts
- • Git, Jira (or similar)
- • SPSS, Minitab
- • OOP, Data Structures & Algorithms
- • Data Analysis, Statistical Modeling
- • Agile methodologies
Education
Computer Science studies (BSc programme) — Open University
Relevant coursework: Algorithms & Data Structures, Software Engineering, OOP, Web Development
Certifications
- Google Cybersecurity Professional Certificate V2, 2025
- Google IT Automation with Python Specialization, 2023
Get In Touch
Interested in collaborating or have a question? Feel free to reach out!