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Introduction to Engineering Data Analytics with R



Due to the current situation, the lecture and exercise will be held online

Short title: IDA

Big Data is currently one of the most important topics in science and research. The preparation, processing and analysis of large and inhomogeneous amounts of data from diverse data sources is playing an increasingly important role in the everyday life of engineers. The ability to filter and process these gigantic amounts of data, to carry out the required analyses and to document the findings accordingly are the basic prerequisites for a successful engineer. In the lecture "Introduction to Engineering Data Analytics with R", the data analysis process from data import to finished documentation is performed by using the R programming language  in the RStudio development environment.

All slides from the lectures and examples are accessible through the ISIS-Plattform.

The programming language R will be practiced in online tutorials provided by DataCamp. The students will get free access to the courses on DataCamp. For more Information feel free to visit: DataCamp

Main Focus

After completing the course, participants will be able to independently perform data analyses in the R programming language in the RStudio development environment using statistical methods, interpret the results and document them. Furthermore, the students are able to prepare the results of their projects and to present and defend them under practical conditions.


The course consists of 2 parts: The weekly lecture and the online tutorials.

Restriction of participation: The course capacity is limited to 300 students.

Therefore, please register at the ISIS page.


For information about registering for the exam see "Registration"

ECTS / Credit Points: 6

Target Audience

Informationstechnik im Maschinenwesen (B. Sc.), Maschinenbau (B. Sc.), Physikalische Ingenieurwissenschaften (B. Sc.), Verkehrswesen (B. Sc.) , Wirtschaftsingenieurwesen (B. Sc.).

Other degree courses are welcome to join!

Desirable Requirements

Basic knowledge of statistical software (R or Python), as well as basic knowledge of mathematics and probability calculus (in each case Abitur knowledge) are desirable, but not mandatory.


The type of examination of this course is "Portfolioprüfung".

For this purpose, the partial performances listed below must be completed with appropriate weighting.

Scoring system
Partial performances
Completing the online tutorials
40 von 100
Completing and presenting the case study
60 von 100

Registration for Examination

For registering for the examination please visit MOSES MTS.




Deadline for Registration
Registration for the lecture 
Registration via ISIS until 22.04.2022. A maximum of 300 Students can participate in the Module.
Registration for the examination
within the first 6 weeks
Class Period: 
22.04.2022 - 22.07.2022
Zoom Webinar
tu-berlin.zoom.us/j/67540149897 Webinar-ID: 675 4014 9897
Kenncode: 438826
Room & Time:
Friday 10.00-12.00 Uhr (Online Lecture & Exercise)
Date of submission and presentation of the case study
Date of submission:  
19.09.2022 - 23.09.2022



Contact and Feedback

Please ask questions via the respective ISIS forum or consult the FAQ.
In exceptional cases, inquiries can be sent directly to the respective contact person via mail (contact form). Telephone consultation is only possible during office hours.

For suggestions please use the feedback funktion of our department..



Office Hours

During the Semester : Check the ISIS page of the course

Zusatzinformationen / Extras

Quick Access:

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Prof. Dr.-Ing. Roland Jochem
Leiter des Fachgebiets
Fachgebiet Qualitätswissenschaft
Institute für Werkzeugmaschinen und Fabrikbetrieb IWF
Faculty V
sec. PTZ 3
Produktionstechnisches Zentrum (PTZ)
Pascalstr. 8-9
10587 Berlin
fon: +49 (0) 30 / 314 22005
fax: +49 (0) 30 / 314 79685


Jan Mayer, M. Sc.
Wissenschaftlicher Mitarbeiter
Institute Institut für Werkzeugmaschinen und Fabrikbetrieb
Faculty Fakultät V - Verkehrs- und Maschinensysteme
sec. PTZ 3
Produktionstechnisches Zentrum (PTZ)
Room Raum PTZ 423
Pascalstraße 8-9
10587 Berlin
+49 30 314-23996