BSc in Data Science
Programme Code: UBDSC
Department: Statistics
For students starting this programme of study in 2023/24
Guidelines for interpreting programme regulations
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.
Paper |
Course number, title (unit value) | |
ÐÓ°ÉÂÛ̳100 |
ÐÓ°ÉÂÛ̳100 is a half unit taken by all students, running across Autumn and Winter Terms in the first year. The course provides one of the marks that is eligible to be included in the calculation of the First Year Average for purposes of classification. Students will choose ONE of the three half-unit options below: | |
ÐÓ°ÉÂÛ̳100A The ÐÓ°ÉÂÛ̳ Course: How can we transform our climate futures? (0.5) | ||
ÐÓ°ÉÂÛ̳100B The ÐÓ°ÉÂÛ̳ Course: How can we control AI? (0.5) | ||
ÐÓ°ÉÂÛ̳100C The ÐÓ°ÉÂÛ̳ Course: How can we create a fair society? (0.5) | ||
Year 1 | ||
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Paper 1 |
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Paper 2 |
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Paper 3 |
ST101A Programming for Data Science (0.5) # and ST115 Managing and Visualising Data (0.5) # | |
Paper 4 |
Courses to the value of 1.0 unit(s) from the following: | |
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AC102 Elements of Financial Accounting (0.5) | |
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AC103 Elements of Management Accounting, Financial Management and Financial Institutions (0.5) | |
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FM101 Finance (0.5) | |
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Year 2 | ||
Paper 5 |
If MA102 or MA103 has not been taken in Year 1: | |
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MA102 Mathematical Proof and Analysis (0.5) # and MA222 Further Mathematical Methods (Linear Algebra) (0.5) # A | |
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OR | |
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If MA102 or MA103 has been taken in Year 1, either: | |
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or | |
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MA203 Real Analysis (0.5) # and MA222 Further Mathematical Methods (Linear Algebra) (0.5) # | |
Papers 6 & 7 |
Courses to the value of 2.0 unit(s) from the following: | |
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Either | |
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ST206 Probability and Distribution Theory (0.5) # and ST211 Applied Regression (0.5) # | |
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and 1.0 unit(s) from the options list below | |
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Or | |
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ST202 Probability, Distribution Theory and Inference (1.0) # and ST211 Applied Regression (0.5) # | |
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and 0.5 unit(s) from the options list below | |
Paper 8 |
MA214 Algorithms and Data Structures (0.5) # and ST207 Databases (0.5) # | |
Year 3 | ||
Paper 9 |
ST310 Machine Learning (0.5) # and ST311 Artificial Intelligence (0.5) # | |
Paper 10 |
Courses to the value of 1.0 unit(s) from the following: | |
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Paper 11 |
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and 0.5 unit(s) from the list of options below | |
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List of options | |
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any 0.5 unit(s) course listed under paper 10 | |
Paper 12 |
Courses to the value of 1.0 unit(s) from the following: | |
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FM300 Corporate Finance, Investments and Financial Markets (1.0) # 6 | |
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any courses listed under papers 10 & 11 | |
Prerequisite Requirements and Mutually Exclusive Options
# means there may be prerequisites for this course. Please view the course guide for more information.
1 : Before taking EC1B3 you must take EC1A3
2 : EC2B3 can not be taken with EC210
3 : Before taking ST301 you must take ST227
4 : Before taking ST303 you must take ST302
5 : ST307 can not be taken with ST205, ST327
6 : Before taking FM300 you must take FM213
7 : ST327 can not be taken with ST307
8 : Before taking ST330 you must take ST302
9 : MA301 can not be taken with MA300
10 : Before taking ST301 you must take ST227
11 : Before taking ST303 you must take ST302
12 : ST307 can not be taken with ST327, ST205
Footnotes
A : Students can obtain exemption from this course if they take MA103 in papers 6&7
B : Students taking this option are exempt from MA102
C : MA203 can only be taken if MA102 or MA103 has been taken under paper 4.
Note for prospective students:
For changes to undergraduate 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 .