The introduction to predictive modelling, variables and their definitions, the stages involved in predictive modelling, smoothing techniques, regression algorithms, clustering algorithms, neural networks, and support vector machines are all covered in this more than two-hour-long course.

There are enough examples and practise exercises to cover every idea. Also taught are the fundamentals of statistics and data visualisation. Data pretreatment, data preparation, model evaluation, and deployment are all given particular priority. This module also covers data distribution, data plotting, and charts, correlation vs. causation, model interpretation, model improvement, etc.

Course Duration:-3h 7m