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Dear Sid

Thank you for your Freedom of Information request of 14 July 2022.

We have completed the compilation of information in response to your
request.

*******FOI request********

I would like to request marking statistics for the optional modules
available to MEng Mathematical Computation students in their third or
fourth year. The required statistics include the mean mark as well as the
5th, 25th, 75th, and 95th percentile marks for the 2021/22 academic year.
I have listed the modules below.

Year 3 Optional Modules:

Functional Programming (COMP0020)

Interaction Design (COMP0021)

Database and Information Management Systems (COMP0022) Networked Systems
(COMP0023) Artificial Intelligence and Neural Computing (COMP0024)
Introduction to Cryptography (COMP0025) Image Processing (COMP0026)
Computer Graphics (COMP0027) Machine Learning for Domain Specialists
(COMP0142) Quantum Computation (COMP0157) Machine Learning for Visual
Computing (COMP0169) Game Theory (ECON0027) Mathematical Methods 3
(MATH0016) Biomathematics (MATH0026) Combinatorial Optimisation (MATH0028)
Mathematical Ecology (MATH0030) Algebraic Number Theory (MATH0035) History
of Mathematics (MATH0038) Algebra 4: Groups and Rings (MATH0053)
Philosophy of Arithmetic and Incompleteness (PHIL0184) Probability and
Statistics II (STAT0005) Stochastic Processes (STAT0007) Commutative
Algebra (MATH0021) Galois Theory (MATH0022) Graph Theory and Combinatorics
(MATH0029) Algebraic Topology (MATH0023)

Year 4 Optional Modules:

Introduction to Cryptography (COMP0025)

Operational Risk Measurement for Financial Institutions (COMP0044)
Affective Computing and Human-Robot Interaction (COMP0053) Computer
Security I (COMP0054) Computer Security II (COMP0055) People and Security
(COMP0056) Malware (COMP0060) Privacy Enhancing Technologies (COMP0061)
Supervised Learning (COMP0078) Graphical Models (COMP0080) Applied Machine
Learning (COMP0081) Bioinformatics (COMP0082) Advanced Topics in Machine
Learning (COMP0083) Information Retrieval and Data Mining (COMP0084)
Statistical Natural Language Processing (COMP0087) Reinforcement Learning
(COMP0089) Requirements Engineering and Software Architecture (COMP0101)
Software Abstractions and Systems Integration (COMP0102) Validation and
Verification (COMP0103) Software Development Practice (COMP0104) Financial
Institutions and Markets (COMP0105) Virtual Environments (COMP0113)
Inverse Problems in Imaging (COMP0114) Computational Modelling for
Biomedical Imaging (COMP0118) Acquisition and Processing of 3D Geometry
(COMP0119) Complex Networks and Web (COMP0123) Multi-agent Artificial
Intelligence (COMP0124) Distributed Systems and Security (COMP0133)
Machine Vision (COMP0137) Cryptocurrencies (COMP0143) AI for Biomedicine
and Healthcare (COMP0172) AI for Sustainable Development (COMP0173)
Practical Program Analysis (COMP0174) Foundations of Artificial
Intelligence (COMP0186) Deep Representations and Learning (COMP0188)
Accountable, Transparent, and Responsible Artificial Intelligence
(COMP0195) Quantum Information and Communication (COMP0196) Mathematical
Methods 4 (MATH0056) Advanced Modelling Mathematical Techniques (MATH0065)
Lie Groups and Lie Algebras (MATH0075) Evolutionary Games and Population
Genetics (MATH0082) Computational and Simulation Methods (MATH0086)
Quantitative and Computational Finance (MATH0088)

*******FOI request********

We can confirm that we do hold some of the information of the description
specified in your request. The information on the modules for which
results exist is provided attached.

As you will see above, where the information is based on the number of
students that is 22 or fewer (indicated by the symbol ˜22), the
information has been withheld because, with such low numbers even
providing this information on an anonymised basis, it may be possible to
identify the individuals, which would make this personal data of third
parties or, if linked with other personal identifiers in the public
domain, would be likely to become personal data. This information has been
withheld under Section 40(2) of the FOIA by virtue of Section 40(3A)(i).

Section 40(2) of the FOIA allows a public authority to withhold
information under the FOIA where (i) the requested information is personal
data relating to someone other than the requester and (ii) its disclosure
would breach any of the Data Protection principles. In this case, we
believe that the requested information could relate to and identify
individuals and therefore would be personal data. The disclosure of these
personal data would not be within the reasonable expectations of the
individuals concerned and it would be unfair to do so; this therefore
breaches the first Data Protection principle.

As the Section 40(2) exemption is an absolute one, there is no need to
conduct a public interest test.

You are free to use any information supplied for your own use, including
for non-commercial research purposes. The information may also be used for
the purposes of news reporting. However, any other type of re-use, for
example by publishing or issuing copies to the public, will require the
permission of the copyright owner.

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Vice-President (Operations)

University College London

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London

WC1E 6BT

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If you have any queries or concerns, please contact me using the details
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Further information on the Freedom of Information Act is available from
the Information Commissioner’s Office:

Wycliffe House

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01625 545700

[2]www.ico.org.uk

[3][email address]

Kind regards

Valeriia Repina

Data Protection and Freedom of Information Adviser

University College London

Legal Services

Data Protection: [4][email address] FOI: [5][UCL request email]

References

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