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Data Analytics MSc 2018/19

General information and guidance about the course is available in the handbook (local access only).

Students are required to take a load of 180 CATS credits. All students must take five core modules totalling 120 CATS, along with an additional 60 CATS from the optional list below. Please note - Optional modules coded ES* and IM* are offered by external departments and places on these modules cannot be guaranteed. It is, therefore, important to register your interest in these modules with the departments concerned as soon as you arrive.

Information about applying for this course is also available.

 

Core Modules

Term

CATS
Credits

Examined/
Assessed

CS908 Research Methods 1 15 A(100)
CS909 Data Mining 2 15 E(40) A(60)
CS910 Foundations of Data Analytics 1 15 E(50) A(50)
CS913 Dissertation Project (MSc Data Analytics) 2, 3 & Summer 60 A(100)
CS917 Foundations of Computing 1 15 A(100)
       

Optional Modules

     
CS402 High Performance Computing 2 15 E(70) A(30)
CS404 Agent Based Systems 2 15 E(50) A(50)
CS413 Image and Video Analysis 1 15 E(70) A(30)
CS414 Semantic Web 1 15 E(70) A(30)
CS912 Sensor Networks and Mobile Data Comms 1 15 E(60) A(40)
CS915 Advanced Computer Security 2 15 E(70) A(30)
CS916 Social Informatics 2 15 E(70) A(30)
CS918 Natural Language Processing 2 15 E(70) A(30)
ES4C8 Signal and Image Processing1 1 15 E(80) A(20)
ES4C4 Optical Communication Systems1 2 15 See course details
ES4D2 Antenna, Propagation and Wireless Communications Theory1 1 15 See course details
ES96T Advanced Wireless Systems and Networks1 2 15 See course details
ES4E7 Information Theory and Coding1 1 15 See course details
IM913 Spatial Methods and Practice in Urban Science2 1 15 See course details
IM919 Urban Data - Theory and Methodology2 2 15 See course details
IM921 Visualisation2 1 15 See course details

Footnotes

1This is provided by the School of Engineering.

2This is provided by the Centre for Interdisciplinary Methodologies. Theser courses require in-person registration. Please see Sharon Hayes for advice.