THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2023/2024

Timetable information in the Course Catalogue may be subject to change.

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DRPS : DPTs : College of Science and Engineering DPTs

Jump to: Year 1, Year 2, Year 3, Year 4

Year 1 Academic year: 2023/24, Starting in: September

A total of 120 credits (the compulsory course worth 20 credits plus 100 credits from the Course Options) must be successfully taken to achieve the PG Diploma. The compulsory course may be taken in either year 1, 2, 3 or 4 of the programme. The Course Options consist of courses from the list below

These courses are limited to students registered on the programme.
We recommend that students take no more than 60 credits in any one year.

With Programme Director approval, students may take up to 20 online learning credits offered within the University of Edinburgh from a related subject area over the course of the programme.

Compulsory courses

Practical Introduction to Data Science

Course options

Leading Technology and Innovation in Organisations

Innovation-driven Entrepreneurship-Data Science, Technology and Innovation

Data security and protection in health and social care

Data Ethics in Health and Social Care

Health Data Science

Data Types and Structures in Python and R

Introductory Applied Machine Learning

Natural Computing

Practical Introduction to High Performance Computing

Message Passing Programming

Threaded Programming

Programming Skills

Software Development

Probability and Statistics

Neuroimaging: Common Image Processing Techniques 1

Neuroimaging: Image Analysis

Neuroimaging: Common Image Processing Techniques 2

Practical Image Analysis 1

Practical Image Analysis 2

Introduction to Python Programming for Data Science

Data Science for Manufacturing (Bayes)

Earth Observation for Sustainable Development Goals

The use and evolution of digital data analysis and collection tools

Social Shaping of Digital Research

Technologies of Civic Participation

Managing Digital Influence

Engaging with Digital Research

Understanding Data Visualisation

Understanding Planetary Health & Data: An Introduction to the Concepts and Themes

AND

Before requesting to take one of these courses, please ensure that the delivery mode is online.

Courses must be delivered online and agreed with the Programme Director, as well as the Course Organiser, prior to course enrolment. The number of additional online courses is limited - for examples of possible courses, please email datascience@ed.ac.uk or check the programme Learn site.

Year 2 Academic year: 2023/24, Starting in: September

A total of 120 credits (the compulsory course worth 20 credits plus 100 credits from the Course Options) must be successfully taken to achieve the PG Diploma. The compulsory course may be taken in either year 1, 2, 3 or 4 of the programme. The Course Options consist of courses from the list below

These courses are limited to students registered on the programme.
We recommend that students take no more than 60 credits in any one year.

With Programme Director approval, students may take up to 20 online learning credits offered within the University of Edinburgh from a related subject area over the course of the programme.

Compulsory courses

Practical Introduction to Data Science

Course options

Leading Technology and Innovation in Organisations

Innovation-driven Entrepreneurship-Data Science, Technology and Innovation

Data security and protection in health and social care

Data Ethics in Health and Social Care

Health Data Science

Data Types and Structures in Python and R

Introductory Applied Machine Learning

Natural Computing

Practical Introduction to High Performance Computing

Message Passing Programming

Threaded Programming

Programming Skills

Software Development

Probability and Statistics

Neuroimaging: Common Image Processing Techniques 1

Neuroimaging: Image Analysis

Neuroimaging: Common Image Processing Techniques 2

Practical Image Analysis 1

Practical Image Analysis 2

Introduction to Python Programming for Data Science

Data Science for Manufacturing (Bayes)

Earth Observation for Sustainable Development Goals

The use and evolution of digital data analysis and collection tools

Social Shaping of Digital Research

Technologies of Civic Participation

Managing Digital Influence

Engaging with Digital Research

Understanding Data Visualisation

Understanding Planetary Health & Data: An Introduction to the Concepts and Themes

AND

Before requesting to take one of these courses, please ensure that the delivery mode is online.

Courses must be delivered online and agreed with the Programme Director, as well as the Course Organiser, prior to course enrolment. The number of additional online courses is limited - for examples of possible courses, please email datascience@ed.ac.uk or check the programme Learn site.

Year 3 Academic year: 2023/24, Starting in: September

A total of 120 credits (the compulsory course worth 20 credits plus 100 credits from the Course Options) must be successfully taken to achieve the PG Diploma. The compulsory course may be taken in either year 1, 2, 3 or 4 of the programme. The Course Options consist of courses from the list below

These courses are limited to students registered on the programme.
We recommend that students take no more than 60 credits in any one year.

With Programme Director approval, students may take up to 20 online learning credits offered within the University of Edinburgh from a related subject area over the course of the programme.

Compulsory courses

Practical Introduction to Data Science

Course options

Leading Technology and Innovation in Organisations

Innovation-driven Entrepreneurship-Data Science, Technology and Innovation

Data security and protection in health and social care

Data Ethics in Health and Social Care

Health Data Science

Data Types and Structures in Python and R

Introductory Applied Machine Learning

Natural Computing

Practical Introduction to High Performance Computing

Message Passing Programming

Threaded Programming

Programming Skills

Software Development

Probability and Statistics

Neuroimaging: Common Image Processing Techniques 1

Neuroimaging: Image Analysis

Neuroimaging: Common Image Processing Techniques 2

Practical Image Analysis 1

Practical Image Analysis 2

Introduction to Python Programming for Data Science

Data Science for Manufacturing (Bayes)

Earth Observation for Sustainable Development Goals

The use and evolution of digital data analysis and collection tools

Social Shaping of Digital Research

Technologies of Civic Participation

Managing Digital Influence

Engaging with Digital Research

Understanding Data Visualisation

Understanding Planetary Health & Data: An Introduction to the Concepts and Themes

AND

Before requesting to take one of these courses, please ensure that the delivery mode is online.

Courses must be delivered online and agreed with the Programme Director, as well as the Course Organiser, prior to course enrolment. The number of additional online courses is limited - for examples of possible courses, please email datascience@ed.ac.uk or check the programme Learn site.

Year 4 Academic year: 2023/24, Starting in: September

A total of 120 credits (the compulsory course worth 20 credits plus 100 credits from the Course Options) must be successfully taken to achieve the PG Diploma. The compulsory course may be taken in either year 1, 2, 3 or 4 of the programme. The Course Options consist of courses from the list below

These courses are limited to students registered on the programme.
We recommend that students take no more than 60 credits in any one year.

With Programme Director approval, students may take up to 20 online learning credits offered within the University of Edinburgh from a related subject area over the course of the programme.

Compulsory courses

Practical Introduction to Data Science

Course options

Leading Technology and Innovation in Organisations

Innovation-driven Entrepreneurship-Data Science, Technology and Innovation

Data security and protection in health and social care

Data Ethics in Health and Social Care

Health Data Science

Data Types and Structures in Python and R

Introductory Applied Machine Learning

Natural Computing

Practical Introduction to High Performance Computing

Message Passing Programming

Threaded Programming

Programming Skills

Software Development

Probability and Statistics

Neuroimaging: Common Image Processing Techniques 1

Neuroimaging: Image Analysis

Neuroimaging: Common Image Processing Techniques 2

Practical Image Analysis 1

Practical Image Analysis 2

Introduction to Python Programming for Data Science

Data Science for Manufacturing (Bayes)

Earth Observation for Sustainable Development Goals

The use and evolution of digital data analysis and collection tools

Social Shaping of Digital Research

Technologies of Civic Participation

Managing Digital Influence

Engaging with Digital Research

Understanding Data Visualisation

Understanding Planetary Health & Data: An Introduction to the Concepts and Themes

AND

Before requesting to take one of these courses, please ensure that the delivery mode is online.

Courses must be delivered online and agreed with the Programme Director, as well as the Course Organiser, prior to course enrolment. The number of additional online courses is limited - for examples of possible courses, please email datascience@ed.ac.uk or check the programme Learn site.

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