Data are everywhere and the ubiquitous availability of huge amounts of data makes it necessary to develop smart data analytics. Out of the plethora of tools that are available for many scientific disciplines this course offers for the common data analyst an easy access to all levels of analysis without deep computer programming knowledge. SDA provides a wide variety of exercises. In addition a full set of slides is provided making it easier for the participants to reanalyze the presented material. The R and Python programming language are becoming the lingua franca of computational data analysis. They are the common smart data analysis software platforms used inside corporations and in academia. Both are OS independent free open-source programs which are popularized and improved by hundreds of volunteers all over the world.
This course presents tools and concepts for unstructured banking and finance data with a strong focus on applications and implementations. It presents the decision analytics in a way that is understandable for non-mathematicians and practitioners who are confronted with day to day number crunching statistical data analysis. All practical examples may be recalculated and modified: software and Quantlets are in www.quantlet.de This course endows the practitioner with ready to use practical tools for smart data analytics.