Data mining and machine learning
MU-TM
Enrollment is Closed
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. Practices on data cleaning, establishing predictive models, association rules, decision tree analysis and cluster analysis. Using of healthcare data sources via data mining to improve operations and decisions in healthcare services. |
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Course information
| Study hours/credits: | 45 hours/ 2 credits |
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| Study hours per week: | 8-9 hours per week |
| Course degree level: | Master degree |
| Course pacing: | Instructor-paced |
| Difficulty level : | Moderate |
| Targeted students: | Students in Graduate diploma and MSc. Program in Biomedical and Health Informatics and others who are interested |
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 techniques to prepare data, and apply appropriate data mining techniques to identify patterns and formulate predictive models |
| LO4: Develop appropriate models and evaluate models using data mining techniques to improve operations and health services |
| LO5: Use data handling techniques to appropriately prepare data for analysis |
Instructors
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Dr. Pimphen Charoen Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University |