Predictive Analytics is a unit that is among the core body of knowledge in data science where students learn the fundamental operations in data science that includes data exploration, classification and clustering models, time series, model validation and deployment, and their applications in predictive analytics. In this unit, students also learn how they can analyse business needs in prediction and provide solutions, team works and communication. Students will implement hands-on models, model testing and validation so that they can develop and deploy appropriate predictive operations and processes to solve real-world problems.

Unit details

Study level:
Credit points:
Unit code:


NIT2151 - Fundamentals of Data Science and

NIT2251 - Machine Learning and Data Mining

Learning Outcomes

On successful completion of this unit, students will be able to:
  1. Apply theories and methods in predictive analytics and professional practices;  
  2. Process and analyse real data sets;  
  3. Adapt modern ethical practice in data analytics; and  
  4. Apply state-of-the-art software and frameworks to propose solutions in predictive analytics.  


Assessment type Description Grade
Test Open book online test 20%
Presentation Group project presentation 10%
Project Group Project based assessment 30%
Case Study Scenario-based in-class problem solving 40%

Where to next?

As part of a course

This unit is studied as part of the following courses. Refer to the course page for information on how to apply for the course.

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