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Applied Machine Learning (MSc)

Informatics (INFR11211), Semester 1, 2023

Week 10 Instructions

Nov 20 · 1 min read

Q&A Session

  • Tomorrow we have the final scheduled Q&A session. We will discuss the structure of the exam and provide some tips for revision. Ask questions on Piazza in advance. 


  • Attend today’s tutorial on Ethics and Fairness. This is a different style of tutorial from the first three, i.e. it is more discussion orientated and will not require much preparation.


  • There are no more pre-recorded lectures. You can start rewatching the previous ones to revise for the exam.  


  • Keep up progress on your coursework, it is due on Nov 23rd at 12pm (afternoon). Submissions instructions will be provided soon.


In this course we will be introducing a number of machine learning methods and concepts, helping to understand how they work, and how to apply them.

Those wanting to conduct research in, and develop, machine learning methods should consider taking MLPR (INFR11130) instead. (Do not take AML and MLPR concurrently though!)
For general information on different machine learning courses at Informatics, see here.

On successful completion of this course, you should be able to:

  1. Explain the scope, goals and limits of ML, and the main sub-areas of the field.
  2. Describe the various techniques covered and where they fit within the structure of the discipline.
  3. Apply the taught techniques to data, to solve ML problems, using appropriate software.
  4. Analyse ML techniques in terms of their limitations and applicability to different problems, as well as potential ethical concerns.
  5. Compare and evaluate the performance of ML techniques using systematic approaches to conducting experiments and assessing scientific hypotheses.