Power and Data Engineering (PDE)
Energy Data Engineering
|Learning objectives / competencies||
The students have an understanding of Big Data Analytics. They know the different process phases in Big Data Analytics (collection, processing, cleansing, explorative statistics, modeling, evaluation and representation of data). They know algorithm applied in the different phases and are able to select suitable methods for practical problems.
Further, students know about real time Big Data analytics. They can clearly differentiate between terms like pattern recognition, machine learning, and deep learning.
|Requirements for awarding credit points||
two written exams 90 minutes
|Credits and Grades||
8 credit points
Sascha Niro M.Sc.
|Frequency||Every 2nd sem.|
Energieinformatik 1/Energy Data Engineering 1