Year 1, Academic year 2015/16, Starting month: September
Notes: Before making your course choices, make sure you have discussed them with your Personal Tutor.
During both years of this programme, students are permitted to take a maximum of 30 credits of courses that are below level 11 or not individually listed below. Over the first two years, at least 10 credits must be selected from each of the three topic groupings: "Machine Learning, Statistics and Optimization", "Databases and Data Management", and "Data Science Applications".
COMPULSORY COURSES
This DPT has 1
compulsory course(s).
|
Code |
Course Name |
Period |
Credits |
|
INFR11034
|
Informatics Research Review |
As available |
20 |
|
COURSE OPTIONS
This DPT has 5
set(s) of course options with the following rules.
Overarching rule collection group: A
Select exactly 40 credits
from these collections:
Select
a minimum of 0 credits and maximum of 40 credits
from the following list of courses, as available
| Code |
Course Name |
Credits |
|
INFR11073
|
Machine Learning & Pattern Recognition (Level 11)
|
10
|
|
INFR11050
|
Probabilistic Modelling and Reasoning
|
10
|
|
INFR11010
|
Reinforcement Learning
|
10
|
|
MATH11085
|
Statistical Theory
|
10
|
|
MATH11086
|
Statistical Regression Models
|
10
|
|
MATH11121
|
Likelihood and Generalized Linear Models
|
10
|
|
MATH11024
|
The Analysis of Survival Data
|
10
|
|
MATH11111
|
Fundamentals of Optimization
|
10
|
|
MATH11030
|
Combinatorial Optimization
|
5
|
|
MATH11031
|
Nonlinear Optimization
|
10
|
|
MATH11010
|
Stochastic Optimization
|
5
|
|
MATH11146
|
Modern Optimization Methods for Big Data Problems
|
10
|
|
INFR10063
|
Introductory Applied Machine Learning
|
10
|
Notes: These are courses in Machine Learning, Statistics, and Optimization open to taught postgraduate students.
AND
Select
a minimum of 0 credits and maximum of 40 credits
from the following list of courses, as available
| Code |
Course Name |
Credits |
|
INFR11088
|
Extreme Computing
|
10
|
|
INFR11015
|
Applied Databases
|
10
|
|
INFR11122
|
Advanced Topics in Foundations of Databases
|
20
|
Notes: These are courses in Databases and Data Management Systems open to taught postgraduate students.
AND
Select
a minimum of 0 credits and maximum of 40 credits
from the following list of courses, as available
| Code |
Course Name |
Credits |
|
INFR11100
|
Text Technologies for Data Science
|
10
|
|
INFR11062
|
Machine Translation (Level 11)
|
10
|
|
INFR11016
|
Bioinformatics 1
|
10
|
|
INFR11005
|
Bioinformatics 2
|
10
|
|
INFR11035
|
Neural Information Processing
|
10
|
|
INFR11033
|
Automatic Speech Recognition
|
10
|
|
LASC11062
|
Speech Synthesis
|
10
|
|
INFR11061
|
Natural Language Understanding (Level 11)
|
10
|
|
INFR09028
|
Foundations of Natural Language Processing
|
10
|
|
INFR11125
|
Accelerated Natural Language Processing
|
20
|
|
INFR11031
|
Advanced Vision (Level 11)
|
10
|
|
MATH11158
|
Optimization Methods in Finance
|
10
|
Notes: These are courses in Unstructured Data and Applications open to taught postgraduate students.
AND
Select
a minimum of 0 credits and maximum of 20 credits
from
Level 11 courses in Schedules A to Q, T and W, as available
Notes: These are courses in all schools other than Medicine or Veterinary Studies. Note this includes courses within the School of Informatics.
AND
Select
a minimum of 0 credits and maximum of 10 credits
from
Level 9 and 10 courses in Schedules A to Q, T and W, as available
Notes: These are courses in all schools other than Medicine and Veterinary Studies. Note this includes courses within the School of Informatics.
|
Year 2, Academic year 2015/16, Starting month: September
Notes: Before making your course choices, make sure you have discussed them with your Personal Tutor. The dissertation requires a period of full-time study after the Semester 2 exams.
During both years of this programme, students are permitted to take a maximum of 30
credits of courses that are below level 11 or not individually listed below. Over the first two years, at least 10 credits must be selected from each of the three topic groupings: "Machine Learning, Statistics and Optimization", "Databases and Data Management", and "Data Science Applications". The dissertation requires a period of full-time study after the exams for the courses.
COMPULSORY COURSES
This DPT has 2
compulsory course(s).
|
Code |
Course Name |
Period |
Credits |
|
INFR11071
|
Informatics Research Proposal |
As available |
20 |
|
|
INFR11077
|
MSc Dissertation (Informatics) |
As available |
60 |
|
COURSE OPTIONS
This DPT has 5
set(s) of course options with the following rules.
Overarching rule collection group: A
Select exactly 40 credits
from these collections:
Select
a minimum of 0 credits and maximum of 40 credits
from the following list of courses, as available
| Code |
Course Name |
Credits |
|
INFR11073
|
Machine Learning & Pattern Recognition (Level 11)
|
10
|
|
INFR11050
|
Probabilistic Modelling and Reasoning
|
10
|
|
INFR11010
|
Reinforcement Learning
|
10
|
|
MATH11085
|
Statistical Theory
|
10
|
|
MATH11086
|
Statistical Regression Models
|
10
|
|
MATH11121
|
Likelihood and Generalized Linear Models
|
10
|
|
MATH11024
|
The Analysis of Survival Data
|
10
|
|
MATH11111
|
Fundamentals of Optimization
|
10
|
|
MATH11030
|
Combinatorial Optimization
|
5
|
|
MATH11031
|
Nonlinear Optimization
|
10
|
|
MATH11010
|
Stochastic Optimization
|
5
|
|
MATH11146
|
Modern Optimization Methods for Big Data Problems
|
10
|
|
INFR10063
|
Introductory Applied Machine Learning
|
10
|
Notes: These are courses in Machine Learning, Statistics, and Optimization open to taught postgraduate students.
AND
Select
a minimum of 0 credits and maximum of 40 credits
from the following list of courses, as available
| Code |
Course Name |
Credits |
|
INFR11088
|
Extreme Computing
|
10
|
|
INFR11015
|
Applied Databases
|
10
|
|
INFR11122
|
Advanced Topics in Foundations of Databases
|
20
|
Notes: These are courses in Databases and Data Management Systems open to taught postgraduate students.
AND
Select
a minimum of 0 credits and maximum of 40 credits
from the following list of courses, as available
| Code |
Course Name |
Credits |
|
INFR11100
|
Text Technologies for Data Science
|
10
|
|
INFR11062
|
Machine Translation (Level 11)
|
10
|
|
INFR11016
|
Bioinformatics 1
|
10
|
|
INFR11005
|
Bioinformatics 2
|
10
|
|
INFR11035
|
Neural Information Processing
|
10
|
|
INFR11033
|
Automatic Speech Recognition
|
10
|
|
LASC11062
|
Speech Synthesis
|
10
|
|
INFR11061
|
Natural Language Understanding (Level 11)
|
10
|
|
INFR09028
|
Foundations of Natural Language Processing
|
10
|
|
INFR11125
|
Accelerated Natural Language Processing
|
20
|
|
INFR11031
|
Advanced Vision (Level 11)
|
10
|
|
MATH11158
|
Optimization Methods in Finance
|
10
|
Notes: These are courses in Unstructured Data and Applications open to taught postgraduate students.
AND
AND
|
|
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