Advanced Predictive Analysis (online)

Topics covered in this module include: 1. Review of Linear Regression 2. Weighted Least Squares 3. Ridge Regression 4. Mixed Effects Models 5. Generalized Linear Models 6. Penalized Splines 7. Generalized Additive Models All the material is supplemented with its implementation in the R programming language

Accordion / FAQ component

Most modules require a 2.2 degree in a related discipline or equivalent professional experience. Should you have any queries regarding your eligibility, please contact us at

N.B. Required to have completed mathematics and statistics modules that contain elements of linear algebra (specifically matrix manipulation) and calculus.

By the end of the module students should be able to:

  • Identify and fit a wide range of statistical models to data
  • Identify important features influencing a given response variable
  • Perform inference and computer uncertainty intervals for advanced predictive statistical models
  • Use the statistical programmes R for generalised linear models, and generalized additive models

Learn from world renowned academic staff in Ireland’s leading, future focused and globally recognised colleges.

Gain an accredited NFQ qualification/micro credential that you may count towards a full award if you so wish in the future.

Previous modules may be used as recognition of prior learning towards Advance Centre degree programmes.

Equip yourself with the latest in demand skillset, tools, know-how and knowledge to succeed in your career.

Gain a competitive edge, influence growth and steer strategic goals in your organisation upon completion of your studies with the Advance Centre.

Yes, if you complete this module it can be credited as part of the MSc Data Analytics or Professional Diploma Data Analytics PT

Detailed Course Information

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