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INFMS  Web- and Data Science Course INF
Lecturers : Prof. Dr. Sven Buchholz    eMail
Term 2
Course Classification : Master Informatik (Sommer-Immatrikulation) CH 4
Language : Deutsch Type VÜS 
Type of examination : PL  Credits
Method of evaluation : written examination 120 min 
Requirements :
Cross References :  
Previous knowledges : Mathematics I 
Aids and special features :  
Teaching aims : Students know important methods and tools for managing and analysing big data. They are confident in applying graph algorithms for analysing the web and social networks. Students know the different dimension of data science. They are competent in solving standard tasks of data science by applying methods/tools from statistics and machine learning. Students know how to model and analyse data streams (unlimited data). 
Contents :

* Foundations of Information Retrieval, Search Engines * Web data, PageRank, Spam * Social Network Analysis, Community Detection * Statistical and Machine Leaning basics for Data Sciece * Algorithms and methods for solving Classification and Clustering * Modelling and Analysing Datastreams (unlimited data) 

Literature : Leskovec, Rajaraman & Ullman: Mining of Massive Datasets, 2019. Russel: Mining the Social Web, 2019. Medjedovic & Tahirovic: Algorithms and Data Structures for Massive Datasets, 2022. Blum, Hopcroft & Kannan: Foundations of Data Science, 2016.  


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