Data science research project - CHE00046M
Module summary
You will work with a project director in an application field to perform exploratory analysis, development and testing of a hypothesis, implementation of the analysis, interpretation of the results, critical evaluation and communication of the findings. This will build on the work you did with your director in the project preparation module. Projects will be offered by each of the contributing departments, although we are also open to students seeking projects from elsewhere in the institution.
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Summer Semester 2025-26 |
Module aims
The aim of the module is to give you experience of performing data science research on a novel research question, of organizing and performing a data science project, of documenting the process and of communicating the results in different formats. You will also learn how to work and communicate with subject domain specialists who may not have the same data science background as you. This will prepare you to implement your own data science projects outside of a learning environment.
Module learning outcomes
Students will be able to:
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Execute a data science research project
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Execute the different stages of data science research from preliminary analysis through to presentation and communication
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Select appropriate data science methods to address a research question
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Critically evaluate and compare the results of data science methods
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Communicate project aims and findings through a written report and oral presentation
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Present scientific data using appropriate visualisations
Module content
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Planning and managing a research project
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Support in applying data science methods to a research question
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Support in communicating the results of a project in oral and written form
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Norms of academic communication
Indicative assessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 75 |
| Oral presentation/seminar/exam | 25 |
Special assessment rules
None
Additional assessment information
Research project report
6000 word written report + computer program
75%
Oral presentation of the project
Oral presentation + questions 25 mins
25%
Indicative reassessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 75 |
Module feedback
Feedback will be provided on a draft of the project report and presentation
Indicative reading
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Introduction to data science : a Python approach to concepts, techniques and applications
Laura Igual, Santi Segui´. Springer 2017 -
Python for data analysis : data wrangling with Pandas, NumPy, and IPython
Wes McKinney. O'Reilly 2017 -
Pro Git
Scott Chacon, Ben Straub. Apress 2014 -
Python and Matplotlib essentials for scientists and engineers
Matt A. Wood. Claypool Publishers 2015 -
Visualization for the Physical Sciences
Lipsa et al. Computer graphics forum, 2012, Vol.31 (8), p.2317-2347 -
Introduction to scientific visualization
Helen Wright. Springer 2007 -
Data Modeling Essentials
Graeme Simsion, Graham Witt. Morgan Kaufmann 2004 - Database design - Adrienne Watt, Nelson Eng. BC Open Textbook Project 2014