TMHG 534 Data mining and machine learning
Free
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 29
- Quizzes 0
- Duration 45 hours
- Skill level All levels
- Language English
- Students 19
- Assessments Yes
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Week 1 : Introduction to data mining / Cluster analysis
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Week 2 : Decision tree analysis
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Week 3 : Clustering Analysis and Decision tree Analysis
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Week 4 : Other data mining methods
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Week 5 : Data preparation
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Weeks 6-7: Final project presentation
