COMP30780

This is an intensive 15-credit,, project-based, data science module. It is designed for students of Computer Science on the Data Science pathway who are not participating in the in-trimester internship programme.

In this module, students will have an opportunity to put their data science skills into practice by implementing a substantial data science project of their own design. Typically this will involve working on a dataset(s) to investigate a meaningful set of research questions, which may be answered from the data. Students are encouraged, within reason, to follow their own interests, and expertise, when it comes to selecting a suitable project topic and dataset.

The project is a collaborative one, and will typically involve groups of 2 students working together on all aspects of the project, from data capture and preparation, through to analysis, and results presentation. The work will be carried out in Python using Jupyter notebooks and the Python 'data-stack', including Pandas, Numpy, Matplotlib etc. Each group will collaborate to produce a final project report and presentation, along with the product of their analysis (a completed Jupyter notebook(s), supplementary code, validated dataset(s) etc.)

Prior to the official start of the module, students will be expected to assemble into suitable groups. The module coordinator will facilitate this in the weeks before the start of the module. In addition, during the field study weeks students (in their groups) will be expected to begin work to identify and define a suitable project proposal and to develop their initial ideas for their proposed project. This will further be facilitated by demonstrator support during the field study weeks.

The module will begin with an intensive "data science bootcamp" in which the students will be taken through an example data analysis project. This will help students to refresh their Python knowledge and to learn how it can be applied to common data science scenarios and tasks. At the conclusion of the bootcamp students groups will make a formal presentation of their own group project proposal.

The practical work for this module will be supported by intensive weekly laboratory sessions in which students will present their progress and engage in relevant problem-based Q&A designed to help them to achieve their goals. Every week groups will be expected to prepare short status updates to discuss their weekly plans and progress.

This is a technically challenging module that requires students to have mastered the basics of Python and its data science packages such as Pandas and Matplotlib.