Predictive Modelling


In this course you’ll use sample data to train and validate a predictive model. You’ll see several supervised learning techniques that can be used to understand your data, then export the preferred models & fit them to new data. You’ll apply key concepts through case-study style learning, with concise lessons and applied assessments.  Created & customized for Chartered Accountants Ireland by

Venue details:  
Online EU, ,
Start date & time:  
03 December 2018 00:00
End date & time:  
01 January 2022 00:00
By registering for this course you have accepted the terms and conditions
Training ticket cost:  
3.00 Training Tickets accepted
CPD hours:  
Speaker details
No speakers have been associated with this event.


Product type:  
CPD online course
Kubicle, Technology and data

Who Should Attend?

This course is suited to advanced learners with general expertise in Alteryx, although you don’t need specific experience of predictive modeling. This course will be of interest to any business professionals, such as accountants, management consultants and analysts who want to understand how their data can be used to make predictions for the future.

Course Overview

This Kubicle course contains 14 lessons, 2 exercises and 1 Exam. It covers the following topics:

  • Introduction to Predictive Modelling
  • Understanding Decision Tree Models
  • Configuring Tree Models
  • Decision Tree Outputs
  • Comparing Decisions Tree Models
  • Validating Our Models
  • The Confusion Matrix
  • Calculating Confusion Matrix Values
  • Boosted Model
  • Forest Model and Neural Networks/li>
  • Naive Bayes
  • Comparing Model Accuracy
  • Exporting the Model Object
  • Deploying the Predictive Models

Key Outcomes

Once you’ve completed this course, you’ll understand how to fit predictive models to your data using Alteryx. You’ll be able to compare the accuracy of a variety of models, then use the preferred models to make predictions for a new dataset. By applying the skills you’ll learn in this course, you’ll be able to understand how your data influences future outcomes in your business.