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The [course_title] course shows you the use of data analytics and big data to health for improving the health care. You will explore the excellent data analytic techniques that can make the diagnosis better and helps you to cure better.

The course covers the three major fields:

  • Healthcare expertise where you learn medical approaches to big data
  • Data analytics- learn the basics of data mining for various healthcare settings.
  • Entrepreneurship – learn to assess when data science-based improvements in health care represent entrepreneurial opportunities

    Assessment

    This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

    Certification

    Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

     

    Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

    • Add the certificate to your CV or resume and brighten up your career
    • Show it to prove your success

    Course Credit: KU Leuven University

Course Curriculum

Module: 1
Welcome Video 00:02:00
Context Case-Finding Type 2 Diabetes10 00:06:00
Health Expenditure Data 00:05:00
Machine Learning 00:09:00
Data Availability 00:05:00
Data Transformation into Machine Readable Data 00:05:00
Identifying Useful Features and Deriving Patterns 00:08:00
Histograms, Curves and Scatterplots 00:06:00
Entrepreneurial Opportunities 00:03:00
The Origins of Opportunity 00:04:00
Module: 2
Opportunity rejection by Incumbents 00:03:00
Conclusion & Reading Suggestion 00:02:00
Introduction to PCR 00:04:00
The Machine Learning Behind 00:07:00
UgenTec Business Case 00:04:00
Data Sources and Formats 00:06:00
Elimination of Inconsistencies and Noise 00:04:00
Clustering and Classification 00:06:00
Decision Trees 00:06:00
Introduction 00:04:00
Module: 3
Understanding how Current Solutions are Appreciated 00:02:00
Competitive Analysis 00:04:00
Industry Analysis 00:03:00
Conclusion & Assignment 00:03:00
Introduction 00:03:00
Data Analysis 00:03:00
Data Sharing 00:04:00
Reliability 00:04:00
Data Organization 00:07:00
Correlations and Regressions 00:06:00
Module: 4
Association Rules 00:04:00
Introduction 00:04:00
Why Market Research can be Misleading 00:03:00
Optimising Your Proposition 00:07:00
Using Market Research to Anticipate Competitive Reactions 00:05:00
Marketing to Prospective Customers 00:07:00
Conclusion & Assignment 00:02:00
Introduction 00:05:00
Workflow I 00:07:00
Workflow II 00:08:00
Module: 5
Data Appreciation 00:04:00
Dealing with Missing Values 00:05:00
Presentation Tools 00:02:00
Density Maps 00:03:00
Introduction 00:02:00
Modelling your Business 00:04:00
Resource Requirements & Capacity Planning 00:05:00
Valuation and Investment Needs 00:09:00
Conclusion & Assignment 00:03:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

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