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Masters Programmes
MSc by Coursework and Research Report in the field of e-Science
This Masters programme aims to train postgraduate students in computational, mathematical and statistical methods to solve data-driven problems. The programme will create opportunities for students in the Computer Science, Statistics, Physics, Electrical Engineering or related fields to gain an interdisciplinary perspective on the emerging fields of Data Science.
MA by Coursework and Research Report in the field of e-Science
This Masters programme aims to train postgraduate students in the use of statistical methods to conduct data-driven research in the social sciences and humanities. The programme will create opportunities for students in the social sciences and humanities to develop an interdisciplinary perspective on the emerging fields of Data Science.
Latest Research
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Bank Credit Card Default Prediction Using Machine Learning Techniques
Researcher: Nompumelelo Sibiya, University of the Witwatersrand, Johannesburg
Supervisors: Mr Rendani Mbuvha, University of the Witwatersrand, Johannesburg -
Population Density and National-Level Governance in Africa
Researcher: Pranish Desai, University of the Witwatersrand, Johannesburg
Supervisor: Professor Rod Alence, University of the Witwatersrand, Johannesburg -
Fingerprint Image Compression using DCT-based Algorithms
Researcher: Promise Magoma, University of Venda
Supervisors: Dr Farai Mlambo, University of the Witwatersrand, Johannesburg -
Using text mining on reviews of Accommodation establishments on TripAdvisor to draw insights on perceived South African weather
Researcher: Subhashini Pillay, University of the Witwatersrand, Johannesburg
Supervisors: Dr Jennifer Fitchett, University of the Witwatersrand, Johannesburg -
Prediction of Customer Churn in Telecommunication using Machine Learning Algorithms
Researcher: Perlate Diala, University of theWitwatersrand, Johannesburg
Supervisor: Dr. Hairong Wang -
Using multisource machine learning to map Prosopis glandulosa in the Griekwastadarea
Researcher: Wessel Bonnet, University of the Witwatersrand, Johannesburg
Supervisors: Elhadi Adam and Turgay Çelik, University of the Witwatersrand, Johannesburg -
Computational Techniques to Predict ICD10 and Diagnosis Code from Native Pathology Images
Researcher: Tshinanne Mbedzi, University Venda
Supervisor: Professor Turgay Çelik and Dr Michael Klipin, University of the Witwatersrand, Johannesburg -
Deep Machine Learning in the search for new bosons at the Large Hadron Collider”
Researcher: Nkateko Baloyi, University of the Witwatersrand, Johannesburg
Supervisors: Professor Bruce Mellado, University of the Witwatersrand, Johannesburg -
Credit Card Fraud Detection using Machine Learning
Researcher: Seleme Shoky, University of Venda
Supervisor: Dr Farai Mlambo, University of the Witwatersrand, Johannesburg -
The use of machine learning to extract a physics model from ATLAS experiment at the LHC
Researcher: Thanyani Gumani, University of Venda
Supervisor: Professor Bruce Mellado, University of the Witwatersrand, Johannesburg -
Comparative Analysis of Logistic Regression over Homomorphically Encrypted Data and Decrypted Data
Researcher: Linhle Mbombo, University of Venda
Supervisor: Professor Augustine Munagi and Professor Turgay Çelik, University of the Witwatersrand, Johannesburg -
Stock Market Forecasting using Wavelet Neural Networks
Researcher: Kgaugelo Mphahlele, University of The Witwatersrand, Johannesburg
Supervisor: Dr Farai Mlambo, University of the Witwatersrand, Johannesburg -
Understanding The Jet Activities In Association With The Dileptons Using Machine Learning Techniques With The Use Of The ATLAS Detector At LHC
Researcher: Mashaka Molepo, University of Venda
Supervisor: Professor Bruce Mellado, University of the Witwatersrand, Johannesburg -
Wind Speed Forecasting Using Long Short-Term Memory (LSTM) Networks
Researcher: Sindisiwe Zulu, University of the Witwatersrand, Johannesburg
Supervisor: Mr Rendani Mbuvha, University of the Witwatersrand, Johannesburg -
The development of Extreme Learning Machine with di-lepton data from the ATLAS detector at the LHC
Researcher: Makgoka Nkoana, University of the Witwatersrand, Johannesburg
Supervisor: Dr Farai Mlambo, University of the Witwatersrand, Johannesburg