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Introduction to Engineering Data Analytics with R

Lupe

Attention:

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.

Main Topics

The course ist structured in:

VL01 - Introduction to Quality Data & Engineering with R

VL02 - Importing Data I

VL03 - Importing Data II

VL04 - Tidy Data

VL05 - Transform Data

VL06 - Joining Data

VL07 - Programing in R

VL08 - Visualize Data with ggplot2

VL09 - Visualize Data with Plotly

VL10 - Visualize Data with Shiny

VL11 - Model Data I 

VL12 - Model Data II / Machine Learning

VL13 - Shiny Advanced

VL14 - Combine Shiny with HTML & CSS & Java Script

VL15 - Dashboard & Casestudy

All slides from the lectures and examples are accessible through the ISIS2-Plattform.

The programming language R will be practiced in online tutorials provided by DataCamp. The students will get free access to the courdes 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.

Structur

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

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

 

For information about registering 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.).

Weitere Studiengänge sind herzlich willkommen!

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.

Evaluation

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
Punkte
Completing the online tutorials
40 von 100
Completing the case study
60 von 100

Registration for Examination

For registering for the examination please visit QISPOS.

Is a registriation over QISPOS not available students have have to register at the responsible examination office. 

Schedule

Deadline for Registration
Registration for the lecture 
no registration needed
Registartion for the examination
within the first 6 weeks
Lecture
Class Period: 
24.04.2020 - 17.07.2020
Room & Time:
Friday 10.00-12.00 Uhr (Online Lecture & Exercise)
Date of submission for the documentation and code of the case study
Date of submission:  
16.08.2020                                

 

 

Contact and Feedback

Please ask questions via the respective ISIS2 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

 By appointment.

Zusatzinformationen / Extras

Quick Access:

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Auxiliary Functions

Verantwortlicher

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
Lupe

Ansprechpartner

Robert Trevino, M. Sc.
Wissenschaftlicher Mitarbeiter
Fachgebiet Qualitätswissenschaft
Institute für Werkzeugmaschinen und Fabrikbetrieb
Faculty V
sec. PTZ3
Produktionstechnisches Zentrum (PTZ)
Room 431
Pascalstr. 8-9
10587 Berlin
+49 (0)30 / 314 21083