Computational Skills for Health and Life Sciences
| Module title | Computational Skills for Health and Life Sciences |
|---|---|
| Module code | HPDM172 |
| Academic year | 2025/6 |
| Credits | 15 |
| Module staff | Professor Neil Vaughan (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 12 | 0 | 0 |
| Number students taking module (anticipated) | 36 |
|---|
Module description
Health data science is a complex field requiring a wide range of computing skills. For example, increasingly, many health datasets are hosted on cloud computing resources and requiring specialist software and multidisciplinary teams to access them. This module complements the Introduction to Python for Health Data Scientists module, with the aim of broadening the scope of the tools available to you as a data scientist. By the end of the module, you will have learned the following skills:
- Cloud computing using the Openstack system
- Computational thinking, including how to design an algorithm and planning programming using pseudocode
- Navigating the Linux command line
- Querying relational databases using SQL
- Ethical and effective use of generative AI
- The benefits of and how to use Git and GitHub for collaborative coding and version control
This module requires no previous knowledge of any of the required skills, although general computer skills will be beneficial.
Module aims - intentions of the module
The aim of this module is to provide a solid foundation in basic computational thinking and provide essential skills in widely used operating systems and computer software.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Demonstrate understanding and competence in fundamental skills for health data science
- 2. Highlight the differences between computational tools and how to combine them to analyse health data
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. Version control for reproducible analysis pipelines
- 4. Using Openstack and the Linux command line to perform advanced computing tasks
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 5. Working collaboratively on developing software
- 6. Dynamically learning new computing skills
Syllabus plan
Whilst the module’s precise content may vary from year to year, an example of an overall structure is as follows:
- An introduction to Linux and OpenStack
- Computational thinking, such as how to plan coding tasks and write pseudocode
- File processing in the Linux command line
- Relational Databases and SQL queries
- Effective and ethical use of generative AI
- Collaborative coding using GitHub
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 36 | 114 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled learning and teaching | 12 | 12 x 1-hour lectures |
| Scheduled learning and teaching | 24 | 12 x 2-hour workshops |
| Guided independent study | 114 | Background reading and preparation for module assessments |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Short answer questions | 300 words | 1-6 | Verbal and written |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 100 | 0 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Coding Assignment | 100 | 2,000 words | 1-6 | Written |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Coding Assignment - 2,000 words (100%) | Coding Assignment - 2,000 words (100%) | 1-6 | Typically within six weeks of the result |
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 30/10/2023 |
| Last revision date | 13/02/2025 |
