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The science of data analytics 353


 
Module code STK 353
Qualification Undergraduate
Faculty Faculty of Economic and Management Sciences
Module content

Data exploration. Data wrangling. Statistical coding. Algorithmic thinking.  Sampling: basic techniques in probability, non-probability, and resampling methods. Text mining and analytics. Machine learning: classification and clustering. Statistical concepts are demonstrated and interpreted through practical coding and simulation within a data science framework.

Module credits 25.00
Service modules Faculty of Natural and Agricultural Sciences
Prerequisites STK 210, STK 220, WST 212 or WST 211, WST 221, WST 212
Contact time 1 practical per week, 3 lectures per week
Language of tuition Module is presented in English
Department Statistics
Period of presentation Semester 2

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