[{"dir":"rprogramming","url":"rprogramming","title":"Introduction to Programming with R","description":"\n \n

\nIntroduction to Programming with R<\/i><\/b><\/q> is a learning resource\nfor programming novices who want to learn programming using the statistical\nprogramming language R<\/i>. One of the mayor strengths of R<\/i> is the\nlarge variety of packages and methods for data analysis. However, the aim of\nthis resource is to learn and practice basic programming and to learn and\nunderstand the basic concepts of programming using base R<\/i>.\nOnly few additional packages will be used and\/or briefly discussed for special\ntasks.\n<\/p>\n

\nThis book<\/q> is specifically taylored to participants of the course\nIntroduction to Programming: Programming in R<\/q> offered by the Digital Science Center (DiSC)<\/a>\nat Universität Innsbruck<\/a>.\n<\/p>\n \n ","image":"static\/rprogramming.jpg","type":"course"},{"dir":"dataanalytics","url":"dataanalytics","title":"Data Analytics","description":"\n\n\n

Data Analytics<\/b><\/q> is a new course organized jointly for the\nbachelor curriculum Wirtschaftswissenschaften<\/q> and the complementary subject area\nDigital Science<\/q> at Universität Innsbruck<\/a> and its\nDigital Science Center (DiSC)<\/a>.<\/p>\n\n

The topics covered encompass multivariate analysis, cluster analysis, independence (A\/B) testing,\n(generalized) linear models, flexible regression.<\/p>\n\n

The main teaching resources are provided in an\nOLAT course<\/a>\n(open to guests). Here, a growing list of accompanying R tutorials will be provided.<\/p>\n\n\n","image":"static\/dataanalytics.png","type":"course"},{"dir":"flexregression","url":"flexregression","title":"Flexible Regression Models","description":"\n \n

\nThis course is about Flexible Regression Models<\/b><\/q>. The course provides detailed\nknowledge of methods for the analysis and modeling of complex data using modern semiparametric\nmethods. The course aims at being able to independently handle complex regression questions, using\nthe statistical software R<\/i>, and to communicate the results. The course includes a variety of\napplied and simulated examples and offers dozens of helpful code snippets that can be used to work\non your own problems.\n<\/p>\n \n ","image":"static\/flexregression.jpg","type":"course"},{"dir":"fabulousjulia","url":"fabulousjulia","title":"Scientific Coding in Julia","description":"\n \n

\nScientific Coding in Julia<\/b><\/q> is a learning resource for all those who are interested in getting a brief glimpse into Julia, Data Science and\/or Parallel Computing. It is designed to fill roughly twelve hours of in-classroom teaching and was prepared for a workshop at the DK CIM & DP DOCC Summerschool 2022 in Obergurgl. However, the material is self-contained and therefore also suitable for self-study.\n<\/p>\n \t\n ","image":"static\/fabulousjulia.jpg","type":"course"},{"dir":"microeconometrics","url":"microeconometrics","title":"Applied Microeconometrics with R","description":"\n\n\n

Applied Microeconometrics with R<\/b><\/q> is an project that will gradually turn\nthe course materials for the Econometrics and Statistics: Microeconometrics<\/q>\ncourse at Universität Innsbruck<\/a>\ninto an online book.<\/p>\n\n

The topics covered roughly follow the book Analysis of Microdata<\/q> by\nWinkelmann & Boes (2009, Springer-Verlag) and encompass: models for categorical responses\n(binary, multinomial, ordered), count data, limited dependent variables, and duration models.<\/p>\n\n\n","image":"static\/microeconometrics.png","type":"course"},{"dir":"meteoapi","url":"https:\/\/meteoapi.discdown.org","title":"Meteo API","description":"\n \n

\nThe Meteo API<\/b><\/q> provides access to\na large climatological data set with decades\nof observations across Austria. Allows\nto request data in different formats to practice\nthe interaction with APIs and encoding XML\/JSON\ndata.\n<\/p>\n

\nThis resource is used in introductory courses\nto data management (R\/Python) such as \nIntroduction to Data Management: Management of Unstructured, Semi-Structured and Structured Data<\/q>\noffered by the Digital Science Center<\/a>\nat Universit\u00e4t Innsbruck<\/a>.\n\n<\/p>\n \n ","image":"meteoapi.jpg","type":"resource"}]