Machine Learning in Business

Synopsis

The rise of machine learning applications has changed the ways different business activities are performed today. This course AIB504 Machine Learning in Business covers popular machine learning techniques and algorithms in business applications, such as customer segmentation, click-through rate (CTR) prediction, churn prediction, customer lifetime value (CLV) prediction, recommendation engines, and machine learning models for time series data. Students will learn about training data, and how to use a set of data to discover potentially predictive relationships.

Level: 5
Credit Units: 5
Presentation Pattern: EVERY REGULAR SEMESTER

Topics

Data preprocessing for Machine Learning
Designing Machine Learning Workflows
Supervised vs Unsupervised Learning
Customer Segmentation
Market Basket Analysis
Click-through Rate (CTR) Prediction
Churn Prediction
Customer Lifetime value (CLV)
Content-Based Recommendations
Collaborative Filtering
Machine Learning for Time Series
Use Cases and Decision-Making

Learning Outcome

Prepare data for machine learning models
Design machine learning workflows
Predict business output variables using machine learning methods
Formulate appropriate machine learning models in business
Evaluate the performance of machine learning models
Improve business decision making via machine learning applications

Part-time Programmes / CET Courses

Singapore University of Social Sciences

Machine Learning in Business