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
Location:
Study level:
Undergraduate
Credit points:
12
Unit code:
NIT3151
Prerequisites
NIT2151 - Fundamentals of Data Science and
NIT2251 - Machine Learning and Data Mining
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Learning Outcomes
| 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
| 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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