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Artificial Intelligence (Module)

Module description

Do you want to learn about artificial intelligence? Study this module if you want to carry out a practical project applying artificial intelligence. You will have an introduction to novel artificial intelligence algorithms for the analysis and predictive modelling of multiple types of healthcare data. Data will include as medical images, genetics, clinical/epidemiological variables, and free text. This module will consist of a minimum of 45 contact hours with teaching taking place between 9am and 5pm from Monday to Friday. An indicative timetable will be available shortly and a detailed timetable for this module will be available on KEATS from June 2020.

Subject specific pre-requisites: 

  • A foundation in programming and coding is required: Proficiency (intermediate level) in Python; a basic understanding of algorithmics and/or algebra
  • Undertaken sufficient mathematical and scientific university studies (equivalent to completing the second year of undergraduate studies in the UK)
  • Applicants must have studied a related subject during their undergraduate studies (i.e. mathematics, physics, engineering, sciences or medicine)

Learning outcomes and objectives

By the end of the module, you should have:

  • understood the foundations of data science, data ingestion, transformation and querying
  • been able to extract meaningful information from large amounts of data
  • developed an understanding of different types of machine learning algorithms, their benefits and drawbacks, and to what situations they should be applied
  • developed an understanding of deep learning and its applications to computer vision tasks
  • applied the learned algorithms and methods to a specific problem, developing an end-to-end solution for it



Staff information

Taught by academics from the Faculty of Life Sciences and Medicine

Teaching pattern

  • Lectures
  • Individual and group lab work
  • Assignments

Module assessment - more information

  • Two workshops, assessed and marked as coursework (40 %)
  • One individual project, including a report and working code (60%)

Key information

Module code

Credit level 6

Assessment coursework presentation/s

Credit value Classes can often be taken for credit towards degrees at other institutions, and are examined to university standards. To receive credit for King's summer classes, contact your home institution to ask them to award external credit. This class is equivalent to an undergraduate degree module and usually awarded 3-4 US credits or 7.5 ECTS.

Semester summer session 2

Study abroad module No