Introduction to Predictive Modelling in Business

Posted 2 years ago by Deakin University

Duration : 2 weeks
Study Method : Online
Subject : Business
Overview
Learn how predictive modelling can help you make better business decisions as you explore the core concepts and CRISP-DM process.
Course Description

Understand how to solve business problems with predictive modelling

The modern world is full of prediction problems in business and economics. On this two-week course, you’ll learn how to solve these problems using the concepts of machine learning and predictive modelling.

You’ll also understand how to identify predictive modelling opportunities with economic data for use within both public and private sectors.

Delve into the CRISP-DM process

One of the most commonly used processes for managing predictive modelling projects in the industry is the Cross Industry Standard Process for Data Mining, or CRISP-DM for short.

CRISP-DM consists of six phases: business understanding, data understanding, data preparation, modelling, evaluation, and deployment. This course will cover these phases at a conceptual level to help you understand their relevance in a corporate environment.

Learn from the experts at Deakin University

Throughout the course, you’ll be guided by the specialists at Deakin University to help you gain a solid understanding of predictive modelling and how it’s used in business.

You’ll finish the course with the knowledge and skills to help you make better business and economic decisions.

This course is designed for professionals, managers, consultants, public servants, research analysts, and other decision-makers who want to incorporate data-driven insights into their decision-making.

Requirements

This course is designed for professionals, managers, consultants, public servants, research analysts, and other decision-makers who want to incorporate data-driven insights into their decision-making.

Career Path
  • Explain the core concepts of predictive modelling
  • Identify predictive modelling opportunities with business data within public and private sectors
  • Apply the steps of the CRISP-DM process at a conceptual level in a corporate environment
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