Data is at the heart of modern organisations, influencing how businesses understand their customers, improve services, manage resources, identify opportunities, and make informed decisions. Data Science brings together data, technology, analytical methods, and problem-solving skills to transform information into meaningful insights and support evidence-based decision-making.  

The PDA Data Science at SCQF Level 7 provides an accessible introduction to working with data. Learners will develop practical skills in collecting, organising, analysing, interpreting, visualising, and communicating data. 

The programme is designed for learners with little or no previous experience of computing, programming, or data science. Through practical activities, learners will develop essential data skills and an understanding of tools and techniques used in modern workplaces. 

The programme also introduces key concepts such as data quality, security, ethics, Artificial Intelligence (AI), machine learning, data visualisation, and data-driven decision-making, providing a strong foundation for further study and career development in data-related fields. 

This qualification comprises two mandatory units and one optional unit, providing learners with a structured and flexible pathway to develop their knowledge and practical skills in data science. 

Learners who successfully complete the required units and meet all relevant assessment requirements can achieve 32 SCQF credit points. Upon successful completion of the qualification, learners will receive an official Qualifications Scotland PDA certificate, formally recognise their achievement and provide nationally recognised evidence of their learning and skills. 

The PDA Data Science SCQF level 7 units/modules are as follows:

There are no formal entry qualification requirements for the PDA Data Science SCQF level 7 qualification.  

• SCQF Level 7 is the recommended entry point for most learners and is designed to be accessible to individuals who have little or no previous experience of data analysis, computing, programming, or data science. 

• Learners are not required to hold a previous qualification in data science, computing, or programming to undertake the Level 7 award.  

• No previous experience of data analysis is essential for entry. 

• Qualifications Scotland guidance indicates that learners would benefit from having the skills, knowledge, and understanding associated with Mathematics at SCQF Level 5 or an equivalent qualification. Relevant experience or qualifications, such as an NPA in Data Science at SCQF Level 6, may also provide useful preparation, but these are recommended rather than mandatory entry requirements. 

• Previous experience of working with spreadsheets is also desirable for Level 7, although specialist knowledge of programming, computing, or data science is not required. 

You do not need to be a programmer, data scientist, or computing specialist to start at SCQF Level 7. The key expectation is that learners have a suitable level of numeracy, communication, problem-solving, and general learning skills to engage successfully with the programme. 

Target Audience

The Level 7 programme is suitable for a broad range of learners, including: 

• Individuals who are new to data analysis and want to develop foundational data skills. 

• Employees who use data as part of their existing job role and want to improve their analytical capabilities. 

• Learners looking to develop practical digital and data skills for the modern workplace. 

• Individuals considering a future career or progression within data analysis. 

• Learners returning to education or professional development who do not have a specialist technical background. 

Learners may progress to further specialised training, education, or employment opportunities in Data Science.  

Individuals wishing to progress to further study at PDA Data Science at SCQF Level 8 or other relevant qualifications. 

This qualification articulates with a number of qualifications. 

• HND Data Science 

• HND Computer Science 

• Technical Apprenticeship in Data Analytics 

• Graduate Apprenticeship in Data Analytics 

• BSc Computer Science 

• BSc Data Science. 

Career Opportunities/ Job Roles 

You could potentially apply for roles such as: 

• Junior Data Analyst 

• Data/Reporting Assistant 

• Business Intelligence Assistant 

• Junior Business Analyst 

• Data Administrator  

• Junior data-related roles within your existing profession

The only learning option available for this course is through our e-learning platform, also known as self-paced learning. This format allows learners to study independently at their own pace, providing flexibility to fit their studies around personal and professional commitments. 

Self-paced e-learning offers several advantages: 

• Flexibility: Learners can access the course materials anytime and anywhere, allowing them to progress through the content at a speed that suits their individual needs. 
• Personalised Learning: Learners can focus on areas where they need more understanding and move quickly through topics, they are already familiar with. 
• Access to Resources: The e-learning mode provides continuous access to multimedia resources, interactive materials, and assessments that can help reinforce learning. 

This approach is ideal for individuals who prefer to manage their own time and learning schedule while still receiving a structured curriculum to guide their progress.

If there are any concerns regarding your eligibility, you may be required to attend an interview with a member of the course team. Additionally, a basic aptitude test will be administered to assess your understanding of the course content. A course consultant will assist you in completing the necessary forms and provide further guidance if needed. 

Course Tuition Fees: 

SAAS Funding: Course funding is available for this course through SAAS PTFG, including the QS exam fee. 

Self-Funding: If any student does not qualify for SAAS funding, they can self-finance this course