GESIS Training Courses
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Scientific Coordination

Dr.
Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Coordination

Loretta Langendörfer M.A.
Tel: +49 221 47694-143

Introduction to Python for Social Scientists

Lecturer(s):
Dr. Arnim Bleier, Indira Sen, Dr. Juhi Kulshrestha

Date: 14.09 - 15.09.2020 ics-file

Location: Online via Zoom

About the lecturer - Dr. Arnim Bleier

About the lecturer - Indira Sen

About the lecturer - Dr. Juhi Kulshrestha

Course description

[This is a 12 hour class.]
 
Data Science is the interdisciplinary science of the extraction of interpretable and useful knowledge from potentially large datasets. In contrast to empirical social science, data science methods often serve purposes of exploration and inductive inference. In this course, we aim to provide a gentle introduction to the Python programming language with a specific emphasis on learning how to work with Python's data science stack. Participants will be provided an introduction to the Python data science stack and Jupyter notebooks, basic concepts of Python, and data exploration and preprocessing with Pandas.


Target group

We offer a starter-level course for Python that provides an introduction to the basics of using the Python programming language for students, researchers or practitioners who want to use Python in their research for tasks in the field of data science. The knowledge obtained in this course provides a starting point for participants to start using Python for exploring and preprocessing data and to perform simple analysis tasks for their own research projects.


Prerequisites

Participants should be willing to study algorithmic approaches on abstract and applied levels. Some previous knowledge of any programming language (like R, C, C++, C#, Java, Syntax-Code in SPSS or Stata) is very advantageous to follow the coursework, though not necessary.

There is no mandatory preliminary preparation needed for this workshop. However there will be some optional preliminary materials provided for those who would like to familiarize themselves with elementary programming concepts and the Jupyter environment, and it is highly recommended that participants go through the prep material before the start of the course. Detailed installation instructions on how to access the development environment will be provided before the start of the course.


Schedule

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