Training

DATA MINING TECHNIQUES Course description This course introduces a wide range of data mining algorithms and both theoretical knowledge and practical skills. Who this course is for? This course is for business analysts and their managers, statisticians, and anyone who has a professional interest in data mining. Prerequisites No prior knowledge of statistical or data mining tools is required. Software InforSense Platform. Oracle Data Mining. Presented by Ali Alkan, Msc. Duration 3 Days. Course contents 1. Introduction to Data Mining 1.1. The short history of data mining. 1.2. Description and application areas of data mining. 1.3. CRISP-DM  (Cross-Industry Standard Process for Data Mining).  2. Predictive Modeling Using Data Mining 2.1. Decision trees. 2.2. Regresyon analysis. 2.3. Artificial neural networks. 2.4. Rule induction algorithms. 3. Variable Selections. 4.Model Evaluation and Implementation. 4.1. Statistical techniques. 4.2. Lift charts. 4.3. ROC charts.     5. Cluster Analysis. 6. Assosication Analysis. 6.1 Basket analysis. 7. Data mining project techniques.