Applied Data Mining with Python
Data is the new gold in this digital era. Like in the old days, it is still should be mined in order to extract the true value of it. This workshop focusses on providing the mandatory background knowledge and hands on experience on applying data mining tools and techniques for identifying patterns and relationships that can help solving business problems through data.
- Identify what kinds of technologies are used for different application.
- Apply data preprocessing techniques.
- Describe data warehouse and OLAP technology.
- Mine frequent patterns and association.
- Apply data classification, clustering, and outlier detection.
Target group: Graduates and professionals
Prerequisite:
- Basic statistics and mathematics with algebra
- Basic knowledge in computer applications and programming will be an advantage.
Learning platform: Python, Weka
(Main Topics, Subtopics supposed to be covered by the course)
• Introduction to data, data sources, and data pipelines for data mining system
o Data warehousing concepts (DBMS, RDBMS, OLTP, OLAP, ETL)
• Methods for data preprocessing in data mining
• Data dimensions and dimensional reduction
o PCA and LDA with python
• Frequent pattern mining algorithms and mining association rules
o GSP, Apriori, and FP Growth Algorithms
• Correlation Analysis
• Data classification and prediction techniques
o Regression, KNN, SVM, ANN with python
• Graph pattern mining techniques, data clustering, and cluster analysis
o K-Means, DBSCAN, and STING with python
• Outlier analysis
👉Account No: 086100130008638
👉Account Name: Institute of Applied Statistics Sri Lanka
👉 People's Bank, Thimbirigasyaya.
Payment should be made on or before 26th November 2023.