DPT: Data Science, Technology and Innovation (Online Learning) (ICL) (PgCert) Part-time Intermittent (PTPGCDSTIN1U)

Jump to: Year 1, Year 2

Year 1 Academic year: 2018/19, Starting in: January

A total of 60 credits (the compulsory course worth 20 credits plus 40 credits from the Course Options) must be successfully taken to achieve PG Certificate. The compulsory course may be taken in either year 1 or 2 of the programme. The Course Options consist of courses in Data Science and Health Care and Medical Informatics.

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

Compulsory courses

Practical Introduction to Data Science

Course options

These are courses in Data Science.

Over the duration of the programme, students should select between 0 and 40 credits of courses from either the Data Science and/or Health Care and Medical Informatics courses. These credits must be completed by the end of Year 2.

We recommend that students take no more than 60 credits in any one year.

Introduction to Java Programming

Advanced Vision

Introductory Applied Machine Learning

Introduction to Vision and Robotics

Image and Vision Computing

Natural Computing

Practical Introduction to High Performance Computing

The use and evolution of digital data analysis and collection tools

Technologies of Civic Participation

Managing Digital Influence

Engaging with Digitial Research

Understanding Data Visualisation

AND

These are courses in Health Care and Medical Informatics.

Over the duration of the programme, students should select between 0 and 40 credits of courses from either the Data Science and/or Health Care and Medical Informatics courses. These credits must be completed by the end of Year 2.

We recommend that students take no more than 60 credits in any one year.

Telemedicine and Telehealth

Ethics and Governance of eHealth

Public Health Informatics

User-Centred Design in eHealth

Research and Evaluation in eHealth

Health Informatics: core technologies and systems

Introduction to Health Informatics and eHealth

Medical Informatics

Neuroimaging: Common Image Processing Techniques 1

Neuroimaging: Common Image Processing Techniques 2

Practical Image Analysis 1

Practical Image Analysis 2