MSc Operational Research and Applied Statistics
MSc Operational Research, Applied Statistics and Risk
MSc Data Science and Analytics
MAT099 (MSc Dissertation) Project Brief
Project title:
Machine Learning & Data Analysis
Number of students to
be allocated to project:
Up to 6
Sponsor organisation:
Cardiff University
Sponsor Supervisor:
Bertrand Gauthier
University Contact:
Joanna Emery (EmeryJL4@cardiff.ac.uk)
The Organisation:
NA
Background:
Machine Learning (ML) and Data Analysis (DA).
Objectives:
This project aims at exploring the application of various DA and ML
Learning (ML) techniques for the analysis and data-based modelisation of
challenging real-life problems. A dataset and its associated problematic will
be provided to the students. The considered problem will be related to
prediction of the properties of some nano materials; the data are supplied
by the School of Chemistry of Cardiff University. (Depending on the will of
the students, some other dataset and problematics might potentially be
considered).
Approach:
A general statistical analysis will first be performed to gain an overall
understanding of the properties of the dataset; the students will in parallel
explore the relevant literature and identify a set of ad hoc ML techniques for
the modelisation of some specific features of the dataset. The selected
techniques will next be implemented, and their efficiency assessed. If time
allows, some optimisation techniques will be applied to the obtained models
in order to help identifying some nano-material configurations of interest.
Deliverables:
Report and sample of the codes produced during the project.
Location of the project:
NA
Key computing skills:
Computations will preferably be performed in R or Python (using Jupyter
notebooks for instance), but any other adequate programming language
and environment can also be considered.
Page 1 of 2
MSc Operational Research and Applied Statistics
MSc Operational Research, Applied Statistics and Risk
MSc Data Science and Analytics
Other key student
competencies:
Curiosity, seriousness and resourcefulness.
Data availability:
Yes.
Any other comments:
No.
Page 2 of 2