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Curricular information is subject to change
1) The key learning objective of this module is for students to gain real-world experience in writing code to manipulate and analyse data.
2) Students will further develop their technical skills in Python, Pandas, and Matplotlib as they collect, clean, analyse and visualise their data and insights.
3) They will gain important experience when it comes to planning a substantial software project, by producing a suitable project plan, prioritising tasks, pursing independent lines of inquiry, and by reporting on their progress on a weekly basis.
4) They will gain valuable experience in preparing and presenting the results of their work as a slide-deck and through an in-class (online) presentation.
5) Students will also learn to work independently (albeit in a supportive and supervised environment) on a substantial coding project.
The purpose of the project is for students to gain valuable experience in building software to obtain and manipulate real-world datasets. This will include writing code to collect and prepare datasets, to answer meaningful research questions, and to visualise the results of their analysis using suitable graphs and charts.
It will be carried out in Python, using Jupyter notebooks, with Pandas and Matplotlib used for data manipulation and visualisation. The module will be supported by weekly status update meetings and technical support sessions, all of which will be held online using video conferencing.
The final deliverables will include the following:
• Completed and documented code (Jupyter notebooks) to collect, clean, analyse, and visualise the specified dataset(s).
• A project plan and weekly status reports.
• A project presentation slide-deck to summarise the work carried out and the results obtained.
• An online presentation of this slide-deck to the class, including a Q&A session.
There are a host of high-quality online resources including:
• https://docs.python.org/3/tutorial/
• https://www.learndatasci.com/tutorials/python-pandas-tutorial-complete-introduction-for-beginners/
• https://pandas.pydata.org/pandas-docs/stable/getting_started/tutorials.html
• https://matplotlib.org/tutorials/index.html
| Student Effort Type | Hours |
|---|---|
| Lectures | 0 |
| Seminar (or Webinar) | 20 |
| Specified Learning Activities | 180 |
| Total | 200 |
Not applicable to this module.
| Description | Timing | Component Scale | % of Final Grade | ||
|---|---|---|---|---|---|
| Project: Project code will be assessed with respect to its adherence to the overall specification and coding best practices. | Unspecified | n/a | Pass/Fail Grade Scale | Yes | 42 |
| Fieldwork: Students will receive a PASS worth 5-credits (33%) for the Industrial Engagement component on the basis that they successfully completed the fieldwork required to secure a successful internship. | Week 1 | n/a | Pass/Fail Grade Scale | Yes | 33 |
| Continuous Assessment: Students will be assessed based on weekly updates on their planning and progress as part of an in-class weekly presentation from each student. A final project presentation will also be assessed. | Throughout the Trimester | n/a | Pass/Fail Grade Scale | Yes | 25 |
| Resit In | Terminal Exam |
|---|---|
| Autumn | No |
• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
Regular feedback will be provided to students, collectively and individually, during weekly update sessions, demonstrator sessions, and one-to-one sessions as appropriate.
| Name | Role |
|---|---|
| Mr Cathal Ryan | Tutor |