Instructors
- Course Staff University of Leuven, Belgium: Arnoud Installé, Postdoctoral Researcher; Amin Ardeshirdavani, Bioinformatician; Dusan Popovic, Postdoctoral Researcher; Marc Claesen, Postdoctoral Researcher.
- Course Staff RWTH Aachen, Germany: Anja Richert, Managing Director Center for Learning & Knowledge Management; Stefan Schröder, Research Assistant & PhD Student; Mohammad Shedadeh, researcher; Anaz Abdelrazeq, Researcher.
- Course Staff University of Maastricht, the Netherlands: Wynand Bodewes, Senior Lecturer.
- Guest Experts: Tom Martens, Managing Director & Co-founder UgenTec; Thomas Beuls, Digital Marketeer UgenTec.
Description
This MOOC illustrates how data analytics has the potential to have a great impact on innovations in the health care domain. We approach the subject by introducing 4 concrete use cases that we study from 3 different perspectives: medical, data analytics and business.
Prerequisites
There are no formal prerequisites to participate in this course.
We welcome health care professionals that are interested in understanding the impact of data and analytics on their field. We welcome data scientists that are interested in discovering use cases of analytics in the health care domain and how they can result in businesses. We welcome entrepreneurs that want to discover the business potential in health care. We welcome anybody interested in learning more about the application of data and analytics in the health care domain, from a data as well as a business perspective.
Course Structure, Duration and Work Load
The duration of this MOOC is four weeks. Each week, a new section is released that covers a particular health use case:
- November 03: Diabetes Case-Finding
- November 10: PCR Analysis
- November 17: Genomics Data Analysis
- November 24: Medical Diagnostic Models
Each section consists of three subsections: (1) introduction to the case, (2) details on the data and analytics techniques involved, (3) insights into the business potential. Each subsection consist of learning videos, optionally offers further reading suggestions and ends with a multiple choice quiz.
The expected work load for each subsection is 2-3 hours. Students that take the full course can thus expect a work load of 6-9 hours per week.
Learning Outcomes and Objectives
- Recognize how health care data analysis can improve health care diagnostics, curing and caring.
- Illustrate the potential of health care data analysis with concrete examples.
- Detect how to acquire, transform, classify, mine and visualize health care data.
- Identify data analytics based entrepreneurial opportunities in health care and quantify its economic value.
- Produce a rigorous business plan for your health care startup.
Grading
This course is graded through multiple choice quizzes. There are 4 sections (released on a weekly basis) that each consist of 3 subsections. At the end of every subsection, there is a final multiple choice quiz. This makes a total of 12 quizzes to complete in this course. The same deadline applies to all quizzes and is November 30th, 11am UTC.
Each question clearly indicates the maximum number of attempts that applies. You will be provided with detailed feedback after filling out the final answer. The passing grade for the course is 60%.