Introduction to Python Programming for Data Science
This online course is aimed at learners with no prior experience of programming. The course will consist of introductory programming learning material presented in the Python language.
This online credit-bearing course is aimed at learners with no prior experience of programming. Therefore, the course will consist of introductory programming learning material presented in the Python language, with a focus on its application to Data Science. All material and teaching will be available online and will consist of:
Exercises to demonstrate the main principles of computer programming through hands-on activities related to data science Online flipped classrooms to provide face-to-face contact time with lecturers, and peer learning activities (pair programming) Group online discussion forum to allow communication between students, and students and lecturers Further information on the course can be found here:
This course consists of introductory programming learning material presented in the Python language and is aimed at people with no prior programming experience.
This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.
The course is aimed at students who have no prior programming experience, but who wish to learn a programming language. It is a Masters-level module, but is still suitable for students without a degree. The minimum entry requirements are an A in either Maths or Physics at Higher/A-level. Students must have not taken any prior programming course.
On completion of this course, the student will be able to:
- Demonstrate a critical understanding of basic Python programming, and its use in managing, analysing and visualising data via data science-oriented modules such as NumPy, SciPy, pandas and matplotlib.
- Demonstrate extensive skill in using iPython and Jupyter Notebooks hosted on CoCalc.
- Plan, conceptualise and implement complete, realistic Python applications to a given specification.
- Develop original and creative code which is functional, efficient, clear, readable and well documented.
- Exercise autonomy and initiative in locating and utilising supporting resources, including 3rd party library code, documentation, and online materials to support development and debugging.
Start Date: 15th January 2024
Course Duration: 17 weeks
Total Hours: 100 ( Online Activities 20, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 78 )
Method of Assessment: Coursework 100 %
Level: This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.
The course fees for 2023/4 are £1,065.
Funding
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.
Eligibility
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 upskilling@ed.ac.uk 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 January 2024 are now closed.
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.
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