Prof. Dr. Andreas Schmidt
Professor, Department of Computer Science and Business Information Systems, Karlsruhe University of Applied Sciences (Germany).
R is not only for statistical computing, but an environment for all sorts of data manipulation, analysis, and mining with very good visualization capabilities like barplots, histograms, heatmaps, graphs, etc. It is available for a wide range of different platforms and easily extensible through its package concept. Major commercial software providers like Oracle and IBM integrate R in their products and provide commercial support for the system. The language R is interpreted and typically used interactively through the command line interpreter or in batch mode. It’s most common data-structures include arrays, vectors, matrices, lists and data-frames and provide a wide range of importing and exporting functions for different sources like files (like text, xml, excel, …), databases, URLs, and different statistical packages like SAS and SPSS. The tutorial will give an introduction to the main data-structures as well as the most important data manipulation and statistical operations. Finally, some of the graphical capabilities will be highlighted. The tutorial will also include hands-on parts, in which the participants use R for simple processing and visualization tasks as well as R as a front-end to visualize data from databases.
1. General Introduction to R
2. Principle data types and operations
3. Accessing external resources
4. Visualization in R
(approximately 1.5-2 hours)
http://www.smiffy.de/ita-2017/ This page contains a short description, how the R-environment can be installed (in case participants want to use their own laptops), as well as the (preliminary) slideset and exercises.
Prof. Dr. Andreas Schmidt is a professor at the Department of Computer Science and Business Information Systems of the Karlsruhe University of Applied Sciences (Germany). He is lecturing in the fields of database information systems, data analytics and model-driven software development. Additionally, he is a senior research fellow in computer science at the Institute for Applied Computer Science of the Karlsruhe Institute of Technology (KIT). His research focuses on database technology, knowledge extraction from unstructured data/text, Big Data, and generative programming. He regularly gives tutorials on international conferences in the field of database technologies, Big Data related topics, and model driven software development.
Dipl.-Ing Dr. Steffen G. Scholz has more than 15 years of R&D experience in the field of polymer micro & nano replication with a special focus on injection moulding and relevant tool-making technologies. He is an expert in process optimization and algorithm design and development for micro replication processes. He studied mechanical engineering with special focus on plastic processing and micro injection moulding and obtained his degree as from the University of Aachen (RWTH). He obtained his PhD from Cardiff University in the field of process monitoring and optimization in micro injection moulding and led a team in micro tool making and micro replication at Cardiff University. Dr. Scholz joined KIT in 2012, where he is now leading the group for process optimization, information management and applications (PIA).
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