Bayes Centre

Introduction to Python Programming for Data Science

This online credit-bearing course is designed to give learners an introduction to programming in the Python language.

Course Summary

This online 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. 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 - Video lectures to explain and expand on more difficult points - Collaborate flipped classrooms to provide face-to-face contact time with lecturers - Group online discussion forum to allow communication between students, and students and lecturer

Further information on the course can be found here:

Introduction to Python Programming for Data Science

Course Delivery Information

Start Date: 17th January 2022
Course Duration: 10 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 intermediate Masters-level course (SCQF Level 11). It develops your skills and/or provides a broad understanding of the subject in some detail. Please see the entry requirements for further details. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.

Entry Requirements

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. 

English Language Requirements

You must be comfortable studying and learning in English if it is not your first language.

Course Fees and Funding

Course fees for 21/22 are £960, but funded places are available for people employed, unemployed or furloughed in Scotland who meet Scottish Funding Council elgibility criteria:

Determining eligibility for a funded place for upskilling takes a number of things into account, including fee status, but also location of employer. SFC provide guidance specifically for upskilling courses:

“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.”

Organisations like UKCISA, and the University, provide guidance on how to determine your fee status:

If your fee status is Scotland Fee Rate, RUK Fee Rate, or EU-EEA Pre/Settled Scotland Fee rate, you may be eligible for a funded upskilling place. To determine this we will look at your fee status, residency information and, where relevant, details of your employer, to confirm whether the employer is based in, or has a significant presence, in Scotland.

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. Please email us at bayes-training@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.

 

Apply Now

Applications for January 2022 are now open.

In order to verify that you meet the entry requirements for this course, you will be required to provide either:

  • a degree certificate/transcript for your highest/most relevant academic qualification, or
  • a CV and reference from an employer (if employed) or professional associate (if unemployed) outlining your suitability for the course

The degree certificate/transcript or CV should be emailed to bayes-training@ed.ac.uk within 24 hours of submitting your application. References should be emailed to the same address (from an institutional/company account if from your employer) within 1 week of submitting your application. 

Once complete, your application will be processed in 1-2 weeks. Applications will be processed 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.

APPLY HERE

Applications will close on 4th January 2022