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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