Predictive Analytics

This subject will commence in 2025

Awards offering Predictive Analytics

This unit is offered as a part of the following awards:

• Bachelor of Business
• Bachelor of Business (Business Analytics)

Unit Content

Outcomes

1. Select, collect, clean, and prepare real-world data for predictive analysis; 
2. Develop predictive models using a variety of techniques, including regression analysis, time series forecasting, and machine learning algorithms, to make accurate predictions based on historical data; 
3. Assess the accuracy and performance of predictive models through the use of appropriate evaluation metrics and validation techniques while adhering to professional and ethical practices; 
4. Solve real-world business problems utilizing predictive insights. 
5. Strategise to make informed decisions in complex and contested commercial environments.

Subject Content

1. Introduction to Predictive Analytics 
2. Data Preparation for Predictive Modeling 
3. Regression Analysis for Predictive Modeling 
4. Classification and Decision Trees 
5. Time Series Forecasting 
6. Clustering and Segmentation 
7. Feature Selection and Engineering 
8. Model Evaluation and Validation 
9. Ensemble Methods in Predictive Analytics 
10. Text and Sentiment Analysis 
11. Predictive Analytics in Business and Marketing
12. Real-World Applications and Case Studies

This course may be offered in the following formats

1. Face to face on site 
2. E-learning (online) 
3. Intensive
4. Extensive

Please consult your course prospectus or enquire about how and when this course will be offered next at Alphacrucis University College.

Assessment Methods

1. Quiz (15%)
2. Project (30%)
3. Report (30%)
4. Presentation (25%)

Prescribed Text

Delen, D. (2020). Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners (2nd ed.). Pearson FT Press. 
Check with the instructor each semester before purchasing any textbooks