Predictive Analytics � Insights of Trends and Irregularities

About This Course

There has been an increasing demand for business analytics, especially in the recent years and this trend is set to experience a continual rise. Predictive analytics is one of the most important areas of business analytics. It is all about extracting information from data and using it to predict future trends and behaviour patterns in businesses. In other words, predictive analytics offers actionable business predictions through mining abundant historical data. It has been widely used in many industries such as banking, insurance, telecom, retail, travel, health care and has shown significant impact on planning and business decision making. Many companies have been turning to predictive analytics to thrive and compete against their competitors.

This course will directly help participants utilise business data more effectively by deriving insights of trends and irregularities from data and applying them for forward-looking predictions. This is realised through building predictive models with appropriate analytical techniques. Ultimately, the company will gain a competitive advantage over its competitors as it would become more proactive in the way it does business and marketing and thereby reduce cost and increase return on investments.

The objective of this course is to introduce participants to the concepts, methods and techniques of predictive analytics. Participants will gain the requisite skills to perform predictive analytics in real-life business scenarios through workshops using either R or SPSS or JMP. The course will assume that the participants have some preliminary knowledge of statistical concepts like regression and logistic regression and some hands on experience of modelling using these techniques, though the course will revisit these concepts to refresh the theory. In case participants have no prior statistical knowledge, it is strongly recommended that they attend the Statistics Bootcamp prior to attending this course.