Data Mining
| Duration | 1 semester |
|---|---|
| State of the module | Compulsory module |
| ECTS | 10 |
| Hours of compulsory in credit hours | 6 |
| Learning outcome/ competencies |
Students understand the difference between processes which confirm and those which identify structures and can differentiate between the functioning of various processes. As well as knowing the systems and implementation requirements of processes, students are able to offer detailed and technically proficient explanations of their respective advantages and drawbacks. Students learn the targeted use of current statistical software. Students have proven their ability to independently apply these processes using computers via concrete and practically relevant scenarios. This requires them to perform data scrubbing and analysis, critically assess the results of their calculations and if necessary, select alternative approaches in order to obtain optimum solutions to the problem at hand. Students are able to enrich data by calculating new key figures in a reasoned manner. As part of a case study, students apply their knowledge to the construction of more complex data mining models, check and evaluate their quality and are able to identify and explain the causes and options for remedying deficiencies. They subsequently use their findings to derive and justify economically sensible measures from the same.
|
| Necessary requirements | None |
| Recommended requirements | MPMD 1.2 Foundations of Data Analytics and statistical Programming |
| Method of examination (applicable are §§ 9-14 RStPO) | tba |