The MSc in Data Science by Coursework and Research Report in the field of Data Science gives students an interdisciplinary perspective on the emerging fields of Data Science. Data Science integrates a number of relevant disciplines such as statistics, computer science, communication, management and sociology to turn data into actionable predictions and insights.
MSc in Data Science Overview
The field of data science by its very nature requires highly skilled individuals who span across both academia and industry. As a result of the above unique skill mix, the demand for data scientists with the required skills has grown exponentially, far exceeding the current supply. Globally and locally, the education system cannot keep up with this demand. WIDS aims to establish various training programs, research opportunities and partnerships between academia and industry, to produce a stream of next-generation data scientists who specifically conduct groundbreaking research in data science by turning data into business value for the industry.
The mission of the University of the Witwatersrand is to grow its global status as a leading research-intensive university and a gateway to research engagement and intellectual achievement in Africa. To this end, “Data Science” has been identified as one of the strategic directions for institutional research. WIDS will support this strategic direction by acting as a hub for enhancing and coordinating multidisciplinary data-driven research, innovation and training activities across the University of the Witwatersrand.
Overall, Data Science is an emerging transdisciplinary field to study ‘data’. Data Science integrates a number of relevant disciplines such as statistics, communication, management and sociology to turn data into actionable predictions and insights. MSc by Coursework and Research Report in the field of Data Science aims to train the students to gain an interdisciplinary perspective on the emerging fields of Data Science. Register online.
Graduates of the program can find data-oriented roles within academic institutions, technology, healthcare companies and the financial sector.
The program includes compulsory and elective modules. Cross-disciplinary data-driven projects are offered both within the university and by a wide range of industrial partners. A candidate must take modules worth 180 credits and must successfully complete the following courses:
Objectives
The Wits Institute of Data Science (WIDS) aims to be a leading interdisciplinary research and training institute with a focus on innovation in data science and machine intelligence. The mission of the University of the Witwatersrand is to grow its global status as a leading research-intensive university and a gateway to research engagement and intellectual achievement in Africa. WIDS will provide a channel through which the above mission can be achieved by promoting intellectual excellence, international competitiveness and local relevance.
Objectives
Act as a focal point (or hub) to organize data science activities around three complementary areas: Mathematical foundations of data science: modelling, statistics, optimization, algorithms, machine learning System aspects of data science: database systems, data cleansing, data management, data integration, data visualization, computational technology Cross -disciplinary collaborations with domain researchers across campus Train and educate the next generation of data scientists. Promote data science innovation through close collaboration with industry and public sector partners
Compulsory courses
Research Report: Data Science (90 credits, Year 2) Research Methods and Capstone Project in Data Science (15 credits, Year 1) Adaptive Computing and Machine Learning (15 credits, Year 1) Large-Scale Computing Systems and Scientific Programming (15 credits, Year 1) Mathematical Foundations of data science (15 credits, year 1) Statistical Foundations of data science (15 credits, year 1) Computational Intelligence (15 credits, year 1)
Electives
Data Privacy and Ethics (15 credits, year 1) Special Topics in Data Science (15 credits, year 1) Natural Language Engineering (15 credits, year 1)
Admission Requirements:
Applicants must have a Bachelor of Science with Honors degree from a relevant discipline in Science (Computer Science, Mathematics, Physics and Statistics) or a relevant level 8 NQF qualification or a relevant professional engineering degree with demonstrable knowledge of the basic principles of algorithms, Computing, Calculus, Linear Algebra, Probability and Statistics.
Applicants require a minimum average of 75 percent.
DEADLINE: 30 NOVEMBER 2021
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