Module code | WST 212 |
Qualification | Undergraduate |
Faculty | Faculty of Economic and Management Sciences |
Module content | Introductory machine learning concepts. Data base design and use. Data preparation and extraction. Statistical modelling using data base structures. Statistical concepts are demonstrated and interpreted through practical coding and simulation within a data science framework. |
Module credits | 12.00 |
NQF Level | 06 |
Programmes |
BCom (Accounting Sciences)
BCom Informatics - Information Systems BCom Investment Management BCom Statistics Bachelor of Information Technology Information Systems [BIT] BSc Computer Science BSc Information and Knowledge Systems BSc Actuarial and Financial Mathematics BSc Mathematical Statistics BSc Meteorology BSc specialising in Mathematics 4-year programme BSc specialising in Meteorology 4-year programme BScAgric Agricultural Economics and Agribusiness Management |
Prerequisites | WST 111, WST 121 or STK 110, STC 122 |
Contact time | 1 practical per week, 2 lectures per week |
Language of tuition | Module is presented in English |
Department | Statistics |
Period of presentation | Semester 1 |
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