Programme And Module Handbook
 
Course Details in 2023/24 Session


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Module Title LI Artificial Intelligence 2
SchoolComputer Science
Department Computer Science
Module Code 06 34255
Module Lead Prof Shan He
Level Intermediate Level
Credits 20
Semester Semester 2
Pre-requisites LC Artificial Intelligence 1 - (06 34238)
Co-requisites
Restrictions None
Contact Hours Lecture-33 hours
Guided independent study-167 hours
Total: 200 hours
Exclusions
Description Artificial Intelligence (AI) and Machine Learning are often applied in situations characterised by various kinds of uncertainty, for example uncertainty in data measurements, missing data or uncertainty in our prior knowledge about the problem. This module will provide principles that enable AI to treat uncertainty consistently in inference, search, optimisation and learning.
Learning Outcomes By the end of the module students should be able to:
  • conceptually understand frameworks for consistent treatment of uncertainty in AI
  • understand principles of inference and fitting to data in AI models under uncertainty
  • describe and understand randomised search and optimisation techniques utilised in AI
Assessment 34255-01 : Examination : Exam (Centrally Timetabled) - Written Unseen (80%)
34255-02 : Continuous Assessment : Coursework (20%)
Assessment Methods & Exceptions Assessment:
Examination (80%),
Continuous Assessment (20%)

Reassessment:
Examination (100%)
Other Edgbaston version of Dubai module 34256
Reading List