KULeuvenX: Data Analytics in Health – From Basics to Business

KULeuvenX: Data Analytics in Health – From Basics to Business

by KU Leuven

Big Data and Health Care Analytics

Offered by KULeuvenX

Course Description

This exciting and comprehensive course is designed to bridge the gap between big data, healthcare, and entrepreneurship. It explores how data analytics can revolutionize healthcare by improving diagnosis, care, and treatment outcomes. This intermediate-level course is perfect for those looking to understand the intersection of data science and healthcare, as well as those interested in identifying entrepreneurial opportunities in this rapidly growing field.

What You'll Learn

  • Application of data analytics to improve healthcare outcomes
  • Fundamentals of data mining in various healthcare settings
  • Techniques for acquiring, transforming, classifying, mining, and visualizing data
  • Identification of data analytics-based entrepreneurial opportunities in healthcare
  • Development of rigorous business plans for healthcare startups
  • Understanding of medical approaches to data and challenges in the field
  • Assessment of the economic value of data-driven healthcare innovations

Who This Course Is For

  • Healthcare professionals looking to leverage data analytics in their practice
  • Data scientists and mathematicians interested in applying their skills to healthcare
  • Entrepreneurs seeking opportunities in the healthcare technology sector
  • Students and professionals interested in the intersection of big data and healthcare
  • Anyone looking to understand how data analytics can improve health outcomes

Real-World Applications

  • Implement data-driven solutions in healthcare settings
  • Develop innovative healthcare technologies and applications
  • Launch startups focused on healthcare analytics
  • Improve diagnostic accuracy and treatment efficacy through data analysis
  • Optimize healthcare processes and reduce costs using big data insights
  • Contribute to research and development in healthcare informatics
  • Advise healthcare organizations on data-driven decision-making strategies

Syllabus

Week 1: Module 1: Diabetes

  • Health data expenditure
  • Machine learning
  • Data transformation
  • Deriving patterns
  • Identifying 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
  • Handling missing data values
  • Density maps
  • Business modeling
  • Requirements and planning
  • Investment needs assessment
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