Computing
Data Science Professional Development Award
Campus OL - Open Learning/Cross Campus
Qualification SCQF Level 8
Study mode Open learning
Start date
Jan 2026
Course enquiry form
Course overview
Are you working with data and want to learn more? Do you have a degree and want to boost your CV with data skills? This course is free if you’ve lived in Scotland for at least 3 years.
Why Learn Data Science?
Data is used in every job—from health care to farming, marketing to cyber security. It helps businesses make wise decisions, improve systems, and create new ideas.
Who Is This Course For?
- People already working in tech or data.
- Anyone with a degree who wants to learn data science.
- You should already know some Python programming.
Course Details
- Level: SCQF Level 8 (same as 2nd year of university).
- Length: 1 year, split into two semesters.
- Breaks: No classes during summer and major holidays.
What you will learn
This course has two units each semester:
- Semester 1: Programming for Data and Working with Data
- Semester 2: Communicating with data and a Data Science project
You will:
- Develop your analysis and communication skills to prepare you for a data professional role.
- Help you appreciate the range of tools and techniques available for data analysis, including packages such as Pyplot, Numpy and Seaborn, and data extraction from sources such as files and API's.
- You will be introduced to using large datasets to gain insights into business data using a range of visualisations and dashboards.
- Be able to create reproducible and automatable analyses of large datasets.
- Apply your knowledge and skills in a collaborative context to the analysis of large and/or complex datasets.
How the course is assessed
- This is an online course in which each group will have its own lecturer, and assessments will be released to students at each stage.
- Assessments are in the form of coursework, programming assignments and reports.
- Semester 1 focuses on building your data skills. There are no formal classes, and you should be able to fit studying around your other commitments, but there are some formal assessment deadlines that you need to meet.
- In semester 2, you will take part in a group project and will be required to attend some informal online workshops, these will allow you to meet the members of your group for the Your final project for this PDA will involve the creation of a group presentation and report, it is essential that you can work as part of a team to complete this course, based on feedback from industry teamwork is one of the key skills in working in data science.
Number of days per week
- New work and tasks will be released every week. It is estimated that this could require 4-6 hours per week of your time, depending on your experience level.
- During the group project, you will collaborate weekly and must attend several face-to-face team sessions.
Entry requirements
- This is an undergraduate-level course, and it is anticipated that those undertaking it will be qualified to HNC, HND, or Degree level, preferably in a related subject area, Technical, Scientific, or Mathematical.
- The coursework requires you to use programming, so you will need to be confident enough to use both Python and R without being taught the basics. There is a group project, and you must work synchronously in a team, with a weekly team meeting at a set time and a work schedule to complete the project.
- If you are unsure about using Python and R, we advise completing the NPA Data Science with Python and R course, which runs from January to June and is free to study for residents of Scotland.
English Proficiency Requirements
IELTS 6.5Progression and Articulation Routes
As this is a new course, we do not have a formally agreed-upon articulation pathway, but the following are suggested progression routes for candidates.
- HND Software Development
- Entry to a data-related degree program
- Progression within your job role
Career options
- This is an ideal course for CPD for those already in employment who need to upskill in data science, computer programming for data, data visualisation or data analytics
- Entry-level data science, data analytics or business analysis roles
Study Options
| Campus | Study mode | Start date |
|---|---|---|
| OL - Open Learning/Cross Campus | Open learning | 26/01/26 |
