Singapore University of Social Sciences

Predictive Modelling

CET Course | SkillsFuture Claimable Course

Predictive Modelling (ANL307)

Applications Open: 01 October 2023

Applications Close: 15 November 2023

Next Available Intake: January 2024

Course Types: Modular Undergraduate Course, SkillsFuture Series

Language: English

Duration: 6 months

Fees: $1391.78 View More Details on Fees

Area of Interest: Business Administration

Schemes: Alumni Continuing Education (ACE)

Funding: SkillsFuture

School/Department: School of Business

Bookmark

Synopsis

ANL307 Predictive Modelling aims to equip students with the skills and knowledge in developing predictive models to solve business problems. The course covers important concepts (such as issues in model construction, evaluation, selection and deployment) that underpin the proper development of useful models. Last but not least, the course also covers applications of predictive modelling using cloud services.

Level: 3
Credit Units: 5
Presentation Pattern: Every January

Topics

  • Introduction to Predictive Modelling
  • Applications of Predictive Modelling
  • Model Construction and Evaluation
  • Model Selection
  • Logistic Regression for making predictions
  • Decision Trees: CHAID and CART
  • Decision Trees: QUEST and C5.0
  • Artificial Neural Networks
  • Ensemble Models
  • Random Forest
  • Support Vector Machine (SVM)
  • Applying Predictive Analytics on Cloud Services

Learning Outcome

  • Discuss various conceptual and practical aspects of applying predictive modelling
  • Appraise the application of predictive modelling
  • Compare different techniques for predictive modelling
  • Construct predictive models using appropriate analytics software
  • Evaluate the performance of predictive models
  • Analyse, interpret and deploy the results or outputs of predictive models
Full-time ProgrammesPart-time Programmes / CET Courses
Back to top

This site uses cookies to offer you a better browsing experience. By continuing to navigate through this site or by clicking “Close”, you are consenting to the use of cookies on your device as described in our privacy policy.

Close
Follow us on
Alumni
Back to top