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Department of Mathematics

Data Science (with an industrial placement year)

(MSc) Data Science (with an industrial placement year)

Entry for 2022

FHEQ level

This course is set at Level 7 (Masters) in the national Framework for Higher Education Qualifications.

No course outline is currently available.

Full-time course composition

YearTermStatusModuleCreditsFHEQ level
1Autumn SemesterCoreAlgorithmic Data Science (969G5)157
  CoreData Science Research Methods (970G1)157
  OptionAdvanced Methods in Molecular Research (806C7)307
  Advanced Numerical Analysis (L.7) (852G1)157
  Applied Natural Language Processing (955G5)157
  Data Analysis Techniques (890F3)157
  Mathematics and Computational Methods for Complex Systems (817G5)157
  Programming in C++ (898F3)157
  Programming through Python (823G5)157
 Spring SemesterCoreData Science Masters Research Proposal (806G1)157
  CoreMachine Learning (934G5)157
  CoreWider Topics in Data Science (905F3)157
  OptionAdvanced Natural Language Processing (968G5)157
  Frontiers in Particle Physics (894F3)157
  Genomics and Bioinformatics (C7120)156
  Image Processing (521H3)157
  Monte Carlo Simulations (865G1)157
  Numerical Solution of Partial Differential Equations (L.7) (845G1)157
  Particle Physics Detector Technology (880F3)157
  Statistical Inference (L.7) (867G1)157
  Wearable Technologies (867H1)157
  Web Applications and Services (944G5)157
YearTermStatusModuleCreditsFHEQ level
2All Year TeachingCorePG Industrial Placement (Data Science) (900G1)1807

Part-time course composition

YearTermStatusModuleCreditsFHEQ level
1Autumn SemesterCoreAlgorithmic Data Science (969G5)157
  CoreData Science Research Methods (970G1)157
  OptionProgramming through Python (823G5)157
 Spring SemesterCoreWider Topics in Data Science (905F3)157
  OptionAdvanced Natural Language Processing (968G5)157
  Frontiers in Particle Physics (894F3)157
  Genomics and Bioinformatics (C7120)156
  Image Processing (521H3)157
  Monte Carlo Simulations (865G1)157
  Numerical Solution of Partial Differential Equations (L.7) (845G1)157
  Particle Physics Detector Technology (880F3)157
  Statistical Inference (L.7) (867G1)157
  Wearable Technologies (867H1)157
  Web Applications and Services (944G5)157
YearTermStatusModuleCreditsFHEQ level
2Autumn SemesterCoreData Analysis Techniques (890F3)157
  CoreMathematics and Computational Methods for Complex Systems (817G5)157
  OptionAdvanced Methods in Molecular Research (806C7)307
  Advanced Numerical Analysis (L.7) (852G1)157
  Applied Natural Language Processing (955G5)157
  Programming through Python (823G5)157
 Spring SemesterCoreData Science Masters Research Proposal (806G1)157
  CoreMachine Learning (934G5)157
  OptionAdvanced Natural Language Processing (968G5)157
  Frontiers in Particle Physics (894F3)157
  Genomics and Bioinformatics (C7120)156
  Image Processing (521H3)157
  Monte Carlo Simulations (L7) (865G1)157
  Numerical Solution of Partial Differential Equations (L.7) (845G1)157
  Particle Physics Detector Technology (880F3)157
  Statistical Inference (L.7) (867G1)157
  Wearable Technologies (867H1)157
  Web Applications and Services (944G5)157

Please note that the University will use all reasonable endeavours to deliver courses and modules in accordance with the descriptions set out here. However, the University keeps its courses and modules under review with the aim of enhancing quality. Some changes may therefore be made to the form or content of courses or modules shown as part of the normal process of curriculum management.

The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.