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Hi šŸ‘‹, I'm Tekano Mbonani

A passionate Data | Statistical | Quantitative Analyst from South Africa

Enthusiastic about merging data insights with the realm of education, I'm currently a Jnr Data Analyst, incharge of everything data related for the Academic Student Tutorial and Excellence Programme (A_STEP) at the Centre for Teaching and Learning (CTL), University of the Free State. Armed with a Bachelor of Science (BSc) Honours degree in Astrophysics and currently completing my Master of Science (MSc) in the same field, I bring a dynamic blend of academic knowledge and practical expertise to the table. My role encompasses selecting and applying advanced statistical methodologies, crafting robust research proposals, and translating intricate data into actionable insights. By doing so, I actively contribute to refining project outcomes and facilitating well-informed decision-making through data.


Additionally, I am a Lecturer and a Researcher. In my previous role, I was a Teaching Assistant for the first entry level modules UFSS1514 and UFSS1526, at the University of the Free State. I have also been a Student Assistant, a Tutor, as well as a Research Assistant at CLT and the Deparment of Physics, University of the Free State.

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Connect with me:

www.linkedin.com/in/tekano-mbonani

Languages and Tools:

bash d3js django dotnet flask git linux matlab mssql mysql postgresql python sqlite

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Tekano Mbonani's Projects

asis icon asis

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.

auto_tutorial_impact_report_generator icon auto_tutorial_impact_report_generator

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.

bootstrap_resample_with_replacement icon bootstrap_resample_with_replacement

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 replacement method to generate artificial light-curves. The code determines the cross-correlation of the artificial light-curves, and uses them for significance.

desktop_notifier icon desktop_notifier

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 tests and exams, it notifies me of time thats passed during the event, without having to look at the watch or clock

light_curve_temp_profile icon light_curve_temp_profile

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

mars icon mars

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.

mars.v1.0.0 icon mars.v1.0.0

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 file.

module-evaluations icon module-evaluations

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

polynomial_regression icon polynomial_regression

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.

powerbi icon powerbi

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

python-scripts icon python-scripts

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

web_scrapper icon web_scrapper

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

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