Multi-modal Data Science For Digital Health level 11
Program start date | Application deadline |
2023-09-18 | 2023-05-05 |
Program Overview
The aim of this course is to provide students with the knowledge to critically appraise and develop decision-support systems for digital health. In collaboration with industry partners, students will be empowered with practical skills and understanding of the domain by diving into use cases which exemplify different aspects of health data analysis.
By participating in this course, learners will have the opportunity to benefit from both a comprehensive introduction multi-modal data science in the digital health domain; and access to experts with experience of applying these techniques to solve real-world problems. The innovative ‘Bring-Your-Own-Project’ approach we propose for module assessment will support learners to apply these skills for their own problems and start building their own professional networks.
Program Outline
Topics
On completion of this module, students are expected to be able to:
- Appraise different types of data science strategies in the context of the digital health domain and its challenges.
- Demonstrate an understanding of machine learning techniques to develop solutions for multi-modal healthcare problems.
- Evaluate the performance of data science techniques within a given business context.
- Visualise and explain the outcomes of data science pipelines for different stakeholders in digital health.
The indicative content covered in this course includes:
Basic data modelling:
identification and selection of features from business data, application of a data science pipeline, evaluation and selection of methodologies.Data analysis techniques:
computer vision, natural language processing/generation, time-series analysis, suitable algorithms for all cases.Context of decision-support systems in digital health domain:
typical use-cases and data, evaluating decision-support systems and their outcomes.Developing decision-support systems:
types of decision-support system, development strategies, alternatives.
The Data Lab
The development of this course has been funded by
The Data Lab
Upskilling Courses
In partnership with the Scottish Funding Council (SFC), our online upskilling short courses have been developed in response to feedback from businesses regarding their people and skills needs and are therefore helpful for individuals considering their employment options as well as organisations looking to upskill their employees. Find out more:
Upskill with our online short courses
Disclaimer
Modules and delivery order may change for operational purposes. The University regularly reviews its courses. Course content and structure may change over time. See our
course and module disclaimer
for more information.Teaching
10 weeks of teaching/learning activity as follows:
Assessment
Independent Study
Staff Delivering on This Course
The course team is comprised of academics who have won multiple STAR awards, and have significant expertise in data science for digital health. Guest lectures showcasing real-life case studies will be delivered by industry partners.
Academic Support
The Inclusion Centre advises and supports students who disclose a sensory or mobility impairment, chronic medical condition, mental health issue, dyslexia and other specific learning differences. Applicants are encouraged to arrange a pre-entry visit to discuss any concerns and to view the facilities.
The Inclusion Centre
Online Learning & Support
All online learning students, benefit from using our collaborative virtual learning environment, CampusMoodle. You will be provided with 24/7 online access to your learning material and resources, along with the ability to interact with your class members and tutors for discussion and support.
CampusMoodle
Study Skills Support
The Study Support Team provides training and support to all students in:
Study Skills Support
Library Support
The Library offers support for your course, including the books, eBooks, and journals you will need. We also offer online reading lists for many modules, workshops and drop-ins on searching skills and referencing, and much more.
University Library
Successful completion of the course will empower individuals to move or expand their portfolio in the data science sector, with a specific focus on digital health. This is a rapidly growing market. According to Life Sciences Scotland, there are more than 250 companies currently working in Medical Technology (MedTech) in Scotland, with over 9,000 people employed in the domain.
Furthermore, the sector is growing rapidly, at a rate of over 8% per annum in the last ten years. The course can also support students to pursue a career in medical technology research and development, either in industrial or academic settings.