Machine Learning

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Compare different methods quantitatively and qualitatively by following fundamental machine learning principles.
• Be able to derive theoretical properties of simple machine learning model and use them to compare different methods.
• Apply appropriate methods to a variety of data sets and learning problems.
• Apply basic criteria that define successful supervised, unsupervised and reinforcement learning.
• Derive theoretical properties of simple machine learning models and use them to compare different methods. 
• Implement discussed learning methods in programming languages using understanding of their theoretical underpinnings.
• Apply appropriate methods using an understand of the statistical underpinnings to various regression and classification algorithms.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.