Overview
This course helps learners understand how to apply supervised learning techniques to business applications. Topics such as different supervised learning techniques, business applications and case studies, build and evaluate the predictive models using real-life business datasets will be covered.
Course Description & Learning Outcomes
At the end of this course, learners will be able to:
Understand several useful supervised learning techniques, e.g. decision tree, linear regression and neural networks
Apply supervised learning techniques to solve real-life business problems, e.g. fraud detection and regression analysis
Identify the business problem, build supervised learning models, compare the model performance and finalise the business solution
Schedule
Start Date: 13 May 2024, Monday
End Date: 15 May 2024, Wednesday
Location: 11 Research Link COM 3, 119391
End Date: 15 May 2024, Wednesday
Location: 11 Research Link COM 3, 119391
Agenda
| Day/Time | Agenda Activity/Description |
|---|---|
| 13 May, 15 May 2024 | 9am – 5.30pm | Business Applications Relying on Supervised Learning |
Pricing
Technology:
Industries:
