Inhaltspezifische Aktionen

GGS Workshop: "Data Preparation with Python"

Wann

19.08.2025 09:00 bis 21.08.2025 17:00 (Europe/Berlin / UTC200)

Wo

Room 001, Licher Strasse 68, 35394 Giessen

Name des Kontakts

Telefon des Kontakts

06419921370

Teilnehmer

Doctoral candidates or postdoctoral researchers doing empirical research or intending to work as data scientists.

Termin zum Kalender hinzufügen

iCal

Instructor:   Dr Tobias Keller
Dates:   August 19, 20, and 21, 2025, 9.00 am – 5.00 pm respectively
Max. participants:   10
Course language:   English (German, if required)
Registration Deadline:   August 5, 2025
ECTS:   3

Objectives

The amount of time required bringing the data into shape for machine learning and artificial intelligence algorithms or statistical analysis is often underestimated. Furthermore, introductions to data science typically focus on the methods and algorithms and do not cover the required data preparation appropriately.

This workshop aims at enabling participants to go beyond the unrealistically clean datasets provided in data science and machine learning tutorials. Instead, participants learn how to handle data as they would face it in real-life situations in research and business, where errors, inconsistencies, incompleteness, duplicates and many more problems are commonplace. They learn how to combine data from different sources and how to perform computations, aggregations, and other typical data preparation steps efficiently. Finally, participants are introduced to special data pre-processing steps required for machine learning.

Having completed this course will give participants an edge in the labour market, where most newcomers have little experience with real-life datasets – especially those aiming for a career in consulting or other areas related to data science and artificial intelligence.

This course is also an ideal complement for participants taking the course “Machine Learning with Python”.

Please note that the knowledge of the topics covered in the previous course, "Introduction to Python (for Data 
Preparation)", is required for participating in this follow-up course.

If participants are not familiar with those concepts and methods, they must participate in the course mentioned above for attending this course.

You can find more details in the syllabus "Data Preparation with Python".