NICF- Predictive Analytics - Insights of Trends and Irregularities

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 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 insurance, telecom, retail, travel, healthcare and has shown positive impact on 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 costs 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 using R and Tableau prior to attending this course.

Key Takeaways

At the end of the course, participants will be able to:

• Identify where predictive analytics can be applied and the benefits which can be derived
• Evaluate the predictive model's objectives and data available
• Design the predictive analytics process
• Assess and select the appropriate testing methods to validate the predictive models
• Analyse the results and communicate the decision to end users

What Will Be Covered

• Introduction to predictive analytics
• How to make predictions using multiple regression models
• Times series modelling and applications
• Introduction to logistic regression modelling
• Predictive modelling using decision trees
• Predictive modelling using neutral networks
• Practical case studies in workshops conducted in R/excel / SPSS / JMP