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KU Leuven University

Data Analytics in Health – From Basics to Business

KU Leuven University via edX

Overview

Many people talk about the promise of “big data” to health care. But how can the application of data analytics to big data actually improve health and health care? We will show that novel data analytics based solutions can result in better diagnosis, better care and better curing. This provides fertile ground for entrepreneurship and the development of new businesses.

In our course we’ll start from the very basics of data analytics, look at different real world approaches and help you to see entrepreneurial opportunities and develop a business plan.

We will cover three important fields:

  • Health care expertise: We will present medical approaches to data and give an overview of challenges where big data based solutions have been developed to improve the efficiency and effectiveness in medicine.
  • Data analytics: We’ll explain the basics of data mining within the context of a wide variety of health care settings, and the types of data and data analysis challenges that you will likely encounter in each. We’ll start with gathering the data, move on to classifying, analyzing and finally visualizing it.
  • Entrepreneurship: You will learn how to assess when data sciences based improvements in health care represent entrepreneurial opportunities. The development of a rigorous business plan is used to help you make that assessment.

Participants with prior experience in the medical field will learn how novel data science applications can improve healthcare, create societal value and how to spot entrepreneurial opportunities.

Participants with experience in data science or mathematics will learn about medical approaches to data and why healthcare is an exciting area to apply and develop data analytics.

Participants interested in launching their startup will learn how big data solutions in health care can provide a solid basis to build great ventures.

Whatever your motivation to enrol in this course, we care about your project and your success - that’s why we will guide you through all parts of this learning journey step by step!

Enter now to see how you can engage in data driven innovation and make an impact on improving care, outcomes and the quality of life.

Syllabus

Week 1: Module 1: Diabetes
Health data expenditure, machine learning, data transformation, deriving patterns, opportunities.

Week 2: Module 2: PCR Analysis
Introduction to PCR, data mining, competitive analysis, industry analysis.

Week 3: Module 3: Genomic Data Analysis
Data sharing, data reliability, association rules, market research, marketing, solution optimization.

Week 4: Module 4: Diagnostic Model Research
Workflow, data missing values, density maps, business modelling, requirements and planning, investment needs.

Taught by

Anja Richert, Stefan Schröder, Mohammad Shehadeh, Anas Abdelrazeq, Wynand Bodewes, Marc Claesen, Arnaud Installé, Tom Martens, Amin Ardeshirdavani, Thomas Beuls and Dusan Popovic

Reviews

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