Quality Enhancement
Introduction to Digital and Data Innovation (SCQF level 6)
Campus OL - Open Learning/Cross Campus
Qualification SCQF Level 6
Study mode Part time
Start date
Aug 2024
Course enquiry form
Course overview
Data Science is essential to living, learning, and working. It revolves around turning insights extracted from data into actionable outcomes. Many people are eager to learn more and understand this topic, and more employers are seeking applicants with experience in Data Science. Utilising the knowledge and skills from this course will help you develop in your current or future job role.
Data Science combines digital and data skills, specific knowledge about a particular topic or subject area, and numeracy skills to extract insights and wisdom from data. The ability to identify the problem to solve, the correct data to use, carry out the analysis, and then implement the outcome requires the integration of these three areas.
The course follows an 18-week structure guided by lecturer support through in-person and online learning. Upon completing this course, you will attain a National Progression Award in Data Science at SCQF level 6. You can advance to the Professional Development Award in Data Science at SCQF level 7, beginning in January 2025.
What you will learn
Data Science is a multidisciplinary subject that combines computer science, statistics, and business knowledge, enabling the generation of insights from data.
The course comprises three units across the 18-week duration:
Data Science:
This unit covers a range of topics related to data science, including the applications of data science, data ethics, methods of data analysis, and how to present data using dashboards and visualisations. You will gain practical skills in analysing large datasets using contemporary software.
Data Citizenship:
You will acquire a range of practical skills and relevant underpinning knowledge. You will learn how to interpret visualisations, such as graphs and charts, and how you can create visualisations from data. Additionally, you will understand how data can be used in society and business for positive and negative effects. Topics will also include data security and the legal rights and responsibilities of data subjects and data owners.
Data Science Project:
You will independently complete an end-to-end data science project. This will involve defining the problem in a project brief, understanding the problem's importance, planning the project, collecting the required data, delivering the analysis, and communicating the findings. Throughout the project, you will document their decisions and findings to create a portfolio of work that constitutes their data science project.
How the course is assessed
- The course is structured to provide a flexible approach to learning, this course is online using video presentations and no live online session will be delivered.
- Assessment work consists of project-based tasks that will be released weekly, requiring an estimated 4-6 hours per week depending on your experience level.
Number of days per week
- Flexible learning using Moodle, an online learning platform and Microsoft Teams.
Entry requirements
- Comfortable using Microsoft Office, particularly spreadsheet packages.
- SCQF level 5 qualification, or relevant experience.
- The course is accessible to individuals with diverse qualifications and work/life experiences.
Information on Tests / Auditions / Interview Requirements
- Completion of a personal statement at the application stage.
English Proficiency Requirements
IELTS 5.5Progression and Articulation Routes
On successful completion of this course and depending on your other skills you could gain entry to the following courses:
- PDA Data Science SCQF Level 7 or 8
- NPA Software Development and Web/Digital Design
- NPA Cyber Security and Networking
- Graduate Apprenticeship in Data Science
- BSc Data Science
Career options
- This qualification provides a great addition to your CV.
- A course for further course progression
- Data science jobs can include data analyst, systems analyst, data scientist, and software engineer.
Study Options
| Campus | Study mode | Start date |
|---|---|---|
| OL - Open Learning/Cross Campus | Part time | 28/08/24 |
