42823 Applied Data Analytics2cp; Online
Requisite(s): 42822 Advanced Data Analytics
Anti-requisite(s): 31250 Introduction to Data Analytics AND 32130 Fundamentals of Data Analytics
Data analytics is the art and science of turning large quantities of usually incomprehensible data into meaningful and commercially valuable information. It is the basis of modern computer analytics and intelligence. It includes a number of IT areas, such as statistical methods for identifying patterns in data and making inferences; database technologies for managing the data sets to be mined; a range of intelligent technologies that derive automatically patterns from data; and visualisation and other multimedia techniques that support human pattern discovery capabilities.
Applied Data Analytics develops the autonomy of learners to plan and implement a data mining project using the most common approach to data mining called cross-industry standard process for data mining, known as CRISP-DM. From pre-processing to deployment of results: representing patterns as rules, functions, cases; model deployment; industry applications, this practical problem based microcredential enables demonstration of analytics expertise and professional communication of analytics.
Detailed subject description.