inline-defaultCreated with Sketch.

This website uses cookies to ensure you get the best experience on our website.

Students
Tuition Fee
USD 1,375
Per course
Start Date
Medium of studying
On campus
Duration
2 months
Program Facts
Program Details
Degree
Courses
Major
Health Informatics | Health Information Technology | Medical Technology
Area of study
Health
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
USD 1,375
Intakes
Program start dateApplication deadline
2023-09-182023-05-05
About Program

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:

  1. Appraise different types of data science strategies in the context of the digital health domain and its challenges.
  2. Demonstrate an understanding of machine learning techniques to develop solutions for multi-modal healthcare problems.
  3. Evaluate the performance of data science techniques within a given business context.
  4. 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:

  • Recorded Lectures: approximately 1 hour/week in total
  • Live Lectures: 2 hours/week
  • Tutorial exercises: a range of guided exercises to help participants further explore the principles covered in lectures.

  • Assessment

  • Regular formative quizzes to check your understanding and progress.
  • Portfolio assessment (comprising group-work as part of a Bring-Your-Own-Project team and individual assessment of completed exercises).

  • Independent Study

  • Materials and exercises are available online, allowing participants to study flexibly and independently at time and place to fit around existing work and life commitments.
  • Online tutor support.

  • 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:

  • Academic writing
  • Study skills (note taking, exam techniques, time management, presentation)
  • Maths and statistics
  • English language
  • Information technology support
  • 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.

    SHOW MORE
    How can I help you today?