ML in Healthcare: Fundamentals & Applications

ML in Healthcare: Fundamentals & Applications

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Explore healthcare data mining methods, theoretical foundations of key techniques, selection criteria, and practical applications with emphasis on data cleansing, transformation, and modeling for real-world problem solving.

Key AI Functions:Machine Learning,Data Mining,Artificial Intelligence

Description for ML in Healthcare: Fundamentals & Applications

Features of Course

  • Investigate data mining techniques that are specifically designed for healthcare environments.
  • Acquire an understanding of the theoretical underpinnings of critical data mining methodologies.
  • Select and implement suitable methodologies, while assessing their advantages.
  • Focus on practical solutions for data purification, transformation, and modeling in healthcare scenarios, while acquiring proficiency in contemporary data mining tools and essential programming skills.
  • Level: Beginner

    Certification Degree: Yes

    Languages the Course is Available: 1

    Offered by: On Coursera provided by Northeastern University

    Duration: 18 hours to complete

    Schedule: Flexible

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