A web-application for the production of evaluation PDF reports, showing tutorial evaluations for the A_STEP tutored modules.

Converting the differential magnitudes of target FSRQs sources into apparent magnitudes, employing apparent magnitudes of standard stars in the field-of-view.

A web application developed for the data collection team at the University of the Free State. The app, named MARS combines weekly attendance register files into a single bulk/aggregated attendance …

ASIS is a web application developed for the compilation of impact report PDF documents for the tutorial programme (A-STEP) at the University of the Free State.

Web_Scrapper was written to download and organise CVs, Transcripts and ID files attached by applicants for the A-STEP tutorial programme.

Showcase app for Theming (Light Theme)

A web application developed for the data collection team at the University of Free State. The app, named MARS combines weekly attendance register files into a single bulk/aggregated attendance file.

An interactive MS Power BI dashboard developed for illustrating and tracking student attendance for tutorials between 2018 - 2023.

A combination of codes developed for the calculation of the cross-correlation confidence intervals, making use of a pair of light-curves. The code conducts a bootstrap random sampling with replacem…

An automated, user-interactive tutorial attendance impact report generator. The code conducts hypothesis testing to compare the student performance with tutorial attendance, and outputs a PDF report.

A repository of python scripts that come in handy in automating day-to-day tasks

An automated Desktop Notifier for Mac OS. The user can edit the notifier to read a message of their liking, and to fit a purpose of their liking. I use the code when I invigilate students during te…

A Python code for fitting the flux variability of light-curves to extract flux rising and falling times.

Polynomial Regression: The code shows examples of machine learning linear and polynomial predictive models, constructed in a loop such that the user can determine the best model for the data.