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Data Mining

2025 · Wahyu Pebrianto

Description

This course teaches techniques for extracting knowledge from large amounts of data using statistical and machine learning methods.

Outline

1. Basic concepts of data mining
2. CRISP-DM: phases and tasks
3. CRISP-DM: algorithms for data mining
4. Data mining from a business perspective and statistics for data mining
5. Introduction to data mining tools
6. Data preparation for regression algorithms with Python
7. Introduction to and application of regression with Python
8. To be announced
9. Data preparation for classification algorithms with Python
10. Introduction to and application of Naive Bayes and SVM with Python
11. Data preparation for clustering algorithms with Python
12. Introduction to and application of KNN and K-Means with Python
13. Data preparation for forecasting with Python
14. Introduction to and application of ANOVA with Python
15. Case study implementation
16. To be announced

Course materials

Videos, slides and notebooks will be added here.