Data Mining and Big Data

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Department of Applied Informatics in Transportation

Synopsis:

Basic terms as databases, relational database, SQL, Big data

Predictive analytics, Text mining, Data mining

Introduction into basic methods of Big data processing Hadoop, Spark

Empirical data analysis in Scala, Python, or Java languages

Large data statistical analysis in R*

Large data processing using Deep learning ANN Caffe, TensorFlow

Symbolic regression and development of other kinds of models using genetic programming algorithms

Introduction into data pre-processing, modelling and interpretation of results

PhD student will chose on of above listed approaches with respect to the subject of its PhD study and applies it in seminar work

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No time-table has been prepared for this course

The course is a part of the following study plans: