A UK 2:1 honours degree or its international equivalent, or a medical degree (MBChB or equivalent).
Relevant work experience may be considered. Please contact us to check whether your experience will be considered by emailing firstname.lastname@example.org. You may be admitted to certificate level only in the first instance.. All applicants must also meet our English language requirements.
Months of entry
January, September, April
Demand is growing for high value data specialists across the sciences, medicine, arts and humanities. The aim of this unique modular online distance learning programme is to enhance existing career paths with an additional dimension in data science.
You can study to Postgraduate Certificate or Postgraduate Professional Development level. It is anticipated that a PG Diploma and MSc will be offered in the future.
This modular online distance learning programme is designed to fully equip tomorrow’s data professionals, offering different entry points into the world of data science – across the sciences, medicine, arts and humanities.
Students will develop a strong knowledge foundation of specific disciplines as well as direction in technology, concentrating on the practical application of data research in the real world.
For the Postgraduate Certificate (PgCert), students must successfully complete a total of 60 credits: Practical Introduction to Data Science (20 credits), and 40 credits from Modular Group A.
For the Postgraduate Professional Development (PgProfDev), students may take a maximum of 50 credits from Modular Group A. These credits will be recognised in their own right for postgraduate level credits or may be put towards gaining a higher award such as a PgCert.
Modular Group A:
- Engaging with Digital Research (10 credits)
- Managing Digital Influence (10 credits)
- Social Shaping of Digital Research (10 credits)
- Technologies of Civic Participation (10 credits)
- Understanding Data Visualisation (10 credits)
- The Use and Evolution of Digital Data, Analysis and Collection Tools (10 credits)
- Introduction to Vision and Robotics (10 credits) (Provisional)
- Advanced Vision (10 credits) (Provisional) (We recommend you take Introduction to Vision and Robotics before taking Advanced Vision.)
- Practical Introduction to High Performance Computing (20 credits)
- Practical Introduction to Data Science (20 credits)
Information for international students
To find out about the support offered to International Students at Edinburgh from arrival to graduation visit: http://wwww.ed.ac.uk/studying/international.
Fees and funding
Visit Scholarships and Student Funding Services at http://www.ed.ac.uk/student-funding.
Qualification and course duration
Course contact details
- Marjorie Dunlop
- 0131 651 7865