Practical Introduction to Data Science (May 2023)
This online course is designed to help you apply ideas from data science to your work. It is designed for technically-minded people and assumes some basic knowledge of computer programming. It introduces ideas from data science, data management and data engineering. It is broad rather than deep, but it aims to provide you with enough practical skills to tackle a real data science problem by the end of the course.
The course is based around recorded lectures, broken into short videos. These recorded lectures will be complemented with a weekly interactive online tutorial with the course organiser which will allow you to ask questions and discuss topics of interest. The concepts and ideas introduced in the lectures are explored in practical exercises to give hands-on experience of applying the techniques.
Further course information can be found in the University's course catalogue:
This course is aimed at those who are technically-minded and already possess a basic knowledge of computer programming.
This is an intermediate Masters-level course (SCQF Level 11). It develops your skills and/or provides a broad understanding of the subject in some detail - some foundational knowledge is required. Please see the entry requirements for further details. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.
A UK 2:1 honours degree, or its international equivalent ideally in a “numerate” discipline (maths, computing, sciences, engineering, economics, …). Other degrees (or no degree) can be accepted with sufficient work experience, e.g. 4 years in a job involved in working with data in a nontrivial way (e.g. administering or querying databases, doing data analysis with spreadsheets, etc.) OR programming/software engineering on a day-to-day basis.
If you are unsure whether you meet these criteria please send your CV to email@example.com
Check whether your international qualifications meet our general entry requirements:
You must be comfortable studying and learning in English if it is not your first language.
- Explain the meaning of data analytics, data science and big data and appreciate the importance of data management
- Describe and apply important data analytics techniques including basic descriptive statistics, clustering and classification
- Identify appropriate data storage mechanisms and analytic techniques for a given problem
- Assess the value of metadata, identifiers and related data management concepts in a given scenario
|Start Date:||1st May 2023|
|Course Duration:||12 weeks|
|Total Hours:||100 (Tutorial Hours 5; Feedback Hours 5; Assessment Hours 20; Independent Study Hours 70)|
|Method of Assessment:||Coursework 100%|
Course fees for 22/23 are £1010, but funded places are available for people employed or unemployed in Scotland who meet Scottish Funding Council elgibility criteria.
Through the Scottish Funding Council (SFC) Upskilling Fund, a limited number of fully-funded places are available on Data Upskilling Short Courses at The University of Edinburgh.
Funded places are available to those who meet SFC fee waiver criteria:
“Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.”
If you are from outside Scotland, you need to have settled status in the UK and meet other residency criteria:
- be ordinarily resident in the United Kingdom, the Channel Islands or the Isle of Man for the three years immediately before course start date, and
- have ‘settled status’ in the UK (as set out in the Immigration Act 1971) at the course start date, and
- be ordinarily resident in Scotland at the course start date.
You can find out more about residency criteria on the SAAS website or in this summary.
Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. You can check your likely fee status here: https://www.ed.ac.uk/tuition-fees/fee-status/work-out Please email us at firstname.lastname@example.org if you would like to discuss your funding eligibility before applying.
Please note that full-time students (including full-time PhD students) are not eligible for funding.
You will receive a certificate of attendance after the final assessment date if you have submitted your coursework.
Applications for May 2023 are now open.
Your application will be processed in 1-2 weeks on a first come, first served basis with priority given to applicants who meet the criteria for a funded place. We aim to email all applicants within 2 weeks of submission regardless of the outcome of their application.
Applications close on 23rd of April.
You may also be able to use credits achieved on this course towards other University of Edinburgh postgraduate programmes, subject to the approval of the relevant Programme Director: