MSc in Geographic Data Science

Page contents > Paper 2 options list | Prerequisite Requirements and Mutually Exclusive Options

Programme Code: TMGEODS

Department: Geography and Environment

For students starting this programme of study in 2023/24

Guidelines for interpreting programme regulations

Full-year programme. Students must take courses to the value of four full units.

Please note that places are limited on some optional courses. Admission onto any particular course is not guaranteed and may be subject to timetabling constraints and/or students meeting specific prerequisite requirements.

Year 1
Paper	Course number, title (unit value)
Paper 1	GY460 Techniques of Spatial Economic Analysis (0.5) ^# *and* GY476 Applied Geographical Information Systems (0.5)
Paper 2	Courses to the value of 1.0 unit(s) from the following:
	GY428 Applied Quantitative Methods (0.5) ^#
	MY470 Computer Programming (0.5)
	MY472 Data for Data Scientists (0.5)
	ST445 Managing and Visualising Data (0.5) ^#
	ST446 Distributed Computing for Big Data (0.5) ^#
	ST449 Artificial Intelligence (0.5) ^#
	ST455 Reinforcement Learning (0.5) ^#
	ST456 Deep Learning (0.5) ^#
	ST457 Graph Data Analytics and Representation Learning (0.5) ^#
	MY474 Applied Machine Learning for Social Science (0.5) ^# ¹ or
	ST443 Machine Learning and Data Mining (0.5) ^# ²
Paper 3	Courses to the value of 1.0 unit(s) from the following:
	GY400 The Economics of Urbanisation (0.5) ^#
	GY404 Inclusive Growth (0.5) ^#
	GY415 Local Capacity and Economic Development Policy (0.5)
	GY426 Environmental and Resource Economics (1.0) ^#
	GY448 Social and Political Aspects of Planning (0.5)
	GY454 Urban Policy and Planning (0.5) ^#
	GY455 Economic Appraisal and Valuation (0.5)
	GY457 Applied Urban and Real Estate Economics (1.0) ^#
	GY473 Economic Development and the Environment (0.5) ^#
	Any course from the Paper 2 options list - not already taken under Paper 2, to the value of 0.5 units
	Paper 2 options list
Paper 4	GY485 Dissertation - MSc Geographic Data Science and MSc Real Estate Economics and Finance (1.0)

Paper 2 options list

GY428 Applied Quantitative Methods (0.5) ^#
MY470 Computer Programming (0.5)
MY472 Data for Data Scientists (0.5)
ST445 Managing and Visualising Data (0.5) ^#
ST446 Distributed Computing for Big Data (0.5) ^#
ST449 Artificial Intelligence (0.5) ^#
ST455 Reinforcement Learning (0.5) ^#
ST456 Deep Learning (0.5) ^#
ST457 Graph Data Analytics and Representation Learning (0.5) ^#
MY474 Applied Machine Learning for Social Science (0.5) ^# ³ or
ST443 Machine Learning and Data Mining (0.5) ^# ⁴

Prerequisite Requirements and Mutually Exclusive Options

# means there may be prerequisites for this course. Please view the course guide for more information.

1 : MY474 can not be taken with ST443

2 : ST443 can not be taken with MY474

3 : MY474 can not be taken with ST443

4 : ST443 can not be taken with MY474

Note for prospective students:
For changes to graduate course and programme information for the next academic session, please see the . Changes to course and programme information for future academic sessions can be found on the .

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