Course description
Modern methods used to analyze data into useful decision making information; various techniques for data exploration and data manipulation; data characteristics in terms of their patterns, correlation, and constraints; predictive models, association rules, decision tree analysis and cluster analysis; examples of applying data mining to improve operations and decisions in healthcare services
Prerequisites
Graduate in Bachelor degree in Health sciences, computer sciences, and ICT.
LO: Learning Outcome
- LO1: Describe the overall data mining process
- LO2: Discuss major theories, practices, and techniques associated with the data mining process
- LO3: Apply appropriate data mining techniques
- LO4: Interpret results obtained from data mining techniques applied
- LO5: Evaluate models using data mining techniques
Course Features
- Lectures 34
- Quiz 0
- Duration 45 hours
- Skill level All levels
- Language English
- Students 53
- Certificate No
- Assessments Yes
Curriculum
- 6 Sections
- 34 Lessons
- 12 Weeks
Expand all sectionsCollapse all sections
- Week 1 : Introduction to data mining / Cluster analysis9
- Week 2 : Decision tree analysis7
- Week 3 : Clustering Analysis and Decision tree Analysis8
- Week 4 : Other data mining methods9
- Week 5 : Data preparation6
- Weeks 6-7: Final project presentation3
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2 Comments
Where can I download the certificate? thank you very much
Hi Jarunee
Please wait until know the results of the course after that you can check in graduate website we will provide the link for download certificate