Big Data Analytics
Integrated course, 3.00 ECTS
The basics of data retrieval and preparation, especially data cleansing methods, are presented at the beginning of the course. After an overview of the Data Analytics Life Cycle, the basic data analytical methods such as clustering, association, regression, classification, time series analysis, text analysis, map reduction and statistical methods are presented. After the elaboration of data bases (distance and similarity measures, neural networks, knowledge representation, textmining, webmining), a final discussion of basic techniques of data visualization, as well as current developments and technologies is presented.
On completion of the course, students have
fundamental deep knowledge about Big-Data systems and analysis.
Recommended or required reading and other learning resources / tools
Books: EMC Education Services, Data Science and Big Data Analytics
Professional Journals: ACM Transactions on Database Systems, Journal of Big Data, BI-SPEKTRUM
Mode of delivery
1 ECTS lecture; 2 ECTS tutorial
Prerequisites and co-requisites
Assessment methods and criteria
Final Exam, Tutorial: Continuous Assessment