Course Description
This course gives beginners an introduction to modern tools for diagnosing disease with patient data. The course covers how Big Data is impacting healthcare, statistical tools for modeling patient data, some applications of these tools, and the future of healthcare (and philosophical implications) regarding AI.
What am I going to get from this course?
Analytic techniques for patient diagnosis, foundational concepts of big data, big data solutions in modern healthcare
Prerequisites and Target Audience
What will students need to know or do before starting this course?
Basic statistics/probability, basic data analytics practices, some (Python) programming knowledge
Who should take this course? Who should not?
Executives, Analysts, Providers, Insurers, and Ancillary Professionals in Healthcare
Curriculum
Lecture 1
Course Overview
Module 2: Making Sense of (Big) Data
Lecture 2
Data in the 21st Century: Where is It All Coming From? 01
Lecture 3
Data in the 21st century: Where is it all coming from? 02
Lecture 4
What makes “big data” big? 01
Lecture 5
What makes “big data” big? 02
Lecture 6
What makes “big data” big? 03
Lecture 7
The importance of data in disease diagnosis: Can an algorithm beat a doctor?
Quiz 1
Making Sense of (Big) Data
Module 3: Techniques to Model and Learn from Data
Lecture 8
How does a statistic “predict” and a machine “learn?” 01
Lecture 9
How does a statistic “predict” and a machine “learn?” 02
Lecture 10
How does a statistic “predict” and a machine “learn?” 03
Lecture 11
Methods to make sense of data 01
Lecture 12
Methods to make sense of data 02
Lecture 13
Methods to make sense of data 03
Lecture 14
Methods to make sense of data 04
Lecture 15
Methods to make sense of data 05
Lecture 16
Evaluating the effectiveness of models in predicting disease 01
Lecture 17
Evaluating the effectiveness of models in predicting disease 02
Lecture 18
Evaluating the effectiveness of models in predicting disease 03
Quiz 2
Techniques to Model and Learn from Data
Module 4: Applications in Patient Disease Diagnosis
Lecture 19
Cancer and heart disease: Predicting major causes of death in the U.S. 01
Lecture 20
Cancer and heart disease: Predicting major causes of death in the U.S. 02
Lecture 21
Population Health Management: A big picture approach to epidemiology
Quiz 3
Applications in Patient Disease Diagnosis
Module 5: Future Applications in Healthcare
Lecture 22
Advanced methods for disease prediction: Neural Networks and AI 01
Lecture 23
Advanced methods for disease prediction: Neural Networks and AI 02
Lecture 24
Wearables and Internet of Things: How do they fit in the future of disease prevention and diagnosis?
Lecture 25
The robot will see you now: Acceptance and ethical concerns of data- driven disease diagnosis
Quiz 4
Future Applications in Healthcare
Lecture 26
Course Summary and Key Point Review
