Compact Course on Data Mining and its Applications

Notice: The course is in German but the slides are in English

Introduction and General Aspects

•  Why Data Mining?
•  What is Data Mining?
•  Difference between Data Mining and Knowledge Discovery in Databases
•  Interdisciplinary aspects of Data Mining
•  Examples of Data Mining Tools
•  Short history of Data Mining, Data Mining rapid development
•  Some European funded projects on Data Mining
•  Scientific Networking and partnership in Data Mining and Machine Learning
•  Conducting of Data Mining projects, optimal structure of a Data Mining team
•  Success factors of Data Mining projects
•  Conferences and Journals on Data Mining

Data Mining Process (CRISP-DM)

•  Business Understanding
•  Data Understanding
•  Data Preparation
•  Modeling
•  Evaluation
•  Deployment

Data Mining and Business Intelligent (BI)

•  Definition of BI
•  Architecture of BI Systems
•  Role of Intelligence in BI
•  Online Analytical Processing (OLAP)
•  Data Warehousing
•  Case Study

Data Mining Algorithms

•  Decision Trees
•  Artificial Neural Networks
•  Association Rules
•  Instance Based Learning (Lazy Learning)
•  Bayesian Methods (Naïve Bayes)
•  Regression Trees
•  Regression Analysis
•  Model Trees
•  Cluster Analysis
•  Logistic Regression

Applications and Case Studies

•  Customer Relationship Management
•  Automotive Industry
•  Healthcare
•  Business and Banking