Predictive Analytics

Unit code: BCO6008 | Study level: Postgraduate
12
(Generally, 1 credit = 10 hours of classes and independent study.)
City Campus
Online Real Time
VU Brisbane
VU Sydney
BCO7000 - Business Analytics and Visualisation
(Or equivalent to be determined by unit coordinator)
Overview
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Overview

The unit is focused on using big data to identify future outcomes and best-assessment of future actions using predictive analytics solutions. Predictive analytics creates a critical competitive advantage for current businesses using data as their most valuable business asset. Using open source environments (R/Python), collaborative development practices and version control (Git/Github) students are exposed to algorithms and machine learning techniques to capture important trends, predict anomalies and forecast business outcomes. The unit is based upon using real-world scenarios and business data. It equips students with solid theoretical foundation of business analytics and builds practical skills. The unit exposes students to industry-based predictive analytics data from Kaggle.

Learning Outcomes

On successful completion of this unit, students will be able to:

  1. Critically analyse the use of predictive analytics approaches in decision making for business organisations to deconstruct complex business problems;
  2. Design reproducible predictive analytics solutions using open source environments (R/Python) and implement collaborative development practices and version control (Git/Github);
  3. Evaluate the selection, implementation and business use of predictive analytics solutions using open source environments (R/Python) in regards to statistical rigour and addressing business goals; and,
  4. Advocate the devised predictive analytics solutions to stakeholders and interpret outcomes to inter-disciplinary audiences.

Assessment

For Melbourne campuses

Assessment type: Test
|
Grade: 25%
Practical exercises (5%,10%, 10%)
Assessment type: Assignment
|
Grade: 35%
Data analytics project: a Kaggle style data analysis (data pre-processing, visualisation and model building)
Assessment type: Assignment
|
Grade: 40%
Group: working with a real-world data set to develop and evaluate a data model - research report (25%) presentation (15%)

Required reading

Selected readings will be made available via the unit VU Collaborate site.

As part of a course

This unit is studied as part of the following course(s):

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