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Veranstaltungen
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Database Systems
| Art |
Vorlesung/Labor |
| Nr. |
M+V2052 |
| SWS |
2.0 |
| Lerninhalt |
- Relational database technologies and products
- Data modeling (ER model and Relational database model)
- Normal forms
- Structured Query Language (SQL)
- Data Control/Definition/Manipulation Language
- Transactions
- Interfaces to database systems
- Time series database systems (basics)
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| Literatur |
- Elvis C. Foster; Shripad Godbole (2016): Database Systems: A Pragmatic Approach, ISBN-13 (pbk): 978-1-4842-1192-2, ISBN-13 (electronic): 978-1-4842-1191-5, DOI 10.1007/978-1-4842-1191-5
- Shefali Naik (2014); Concepts of database management system; Delhi : Pearson; ISBN 9789332537231, 9332537232; Nummer 1892760444 (K10Plus-Nummer)
- Mike Fleckenstein, Lorraine Fellows (2018): Modern Data Strategy; Springer International Publishing AG; Druck ISBN 9783319689920, E-Book ISBN 9783319689937
- Saake, Gunter; Heuer, Andreas; Sattler, Kai-Uwe (2018): Datenbanken - Konzepte und Sprachen. 6. Aufl. Frechen: mitp.
- Elmasri, Ramez A.; Navathe, Shamkant B.; Shafir, Angelika (2011): Grundlagen von Datenbanksystemen. Bachelorausg., 3., aktualisierte Aufl., [Nachdr.]. München: Pearson Studium (IT - Informatik)
- Kemper, Alfons Heinrich; Eickler, André (2015): Datenbanksysteme. Eine Einführung. 10., erweiterte und aktualisierte Auflage. Berlin, Boston: De Gruyter Studium.
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Energy Data Engineering 2
| Art |
Vorlesung/Labor |
| Nr. |
M+V3050 |
| SWS |
4.0 |
Energy Data Engineering 1
| Art |
Vorlesung/Labor |
| Nr. |
M+V3049 |
| SWS |
4.0 |
| Lerninhalt |
- Data Mining Terminology and concepts
- Data Mining process models
- Exploratory Data Analysis
- Descriptive Statistics
- Classification and Regression Models (Decision Trees, Random Forest, K-nearest neighbours, Naive Bayes, ...)
- Model Evaluation and Comparison
- Clustering
- Linear Regression
- Time Series Analysis
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| Literatur |
Reddy, T. Agami, Applied data analysis and modeling for energy engineers and scientists; Springer Science & Business Media, 2011
Witten, I. H. and Hall, M. A., Data mining: Practical machine learning tools and techniques, 3rd ed.
Burlington, MA: Morgan Kaufmann, 2011
Han, J., Kamber, M., and Pei, J., Data Mining: Concepts and Techniques, 3rd ed. Burlington: Elsevier Science, 2011
Hastie, T., Tibshirani, R., and Friedman, J. H., The elements of statistical learning: Data mining,
inference, and prediction, 2nd ed. Springer series in statistics. New York: Springer, 2009
Alpaydın, E., Maschinelles Lernen. München: Oldenbourg, 2008. |
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