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Verena Kunz

Administrative Coordination

Noemi Hartung
Tel: +49 621 1246-211

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Introduction to Python

About
Location:
Online via Zoom
 
General Topics:
Data Analysis; Computational Social Science
Course Level:
Beginner
Format:
Workshop
Software used:
none
Duration:
3 days
Language:
English
Fees:
Students: 300 €
Academics: 450 €
Commercial: 900 €
 
Keywords
Additional links
Lecturer(s): Hannah Béchara, Paulina Garcia Corral

About the lecturer - Hannah Béchara

About the lecturer - Paulina Garcia Corral

Course description

This course is an introduction to programming with Python with a special focus on data analysis and machine learning, for which the programming language is known to be particularly powerful. Through morning lectures and afternoon applied sessions, the participants will learn the fundamentals of programming as well as how to use Python as a powerful tool for data wrangling, data visualization, and data analysis. The objectives of the course are to give participants the tools that all basic programming tasks need as well as an overview of the specific topics needed to carry out analyses for multiple data types.


Target group

Participants will find the course useful if:
  • they are beginners with no previous programming experience who are interested in learning Python for data science and computational social science applications


    • Learning objectives

    By the end of the course participants will:
  • master the fundamentals of writing Python scripts
  • learn core scripting elements such as variables and flow control structures
  • discover how to work with lists and sequence data
  • write Python functions to facilitate code reuse
  • use Python to read and write files
  • learn how to use Pandas, Matplotlib, and other useful libraries for data manipulation, analysis, manipulation and more
    •  
    Organizational structure of the course
    Morning sessions will be lecture-based, with introduction to fundamentals accompanied by quick exercises to practice the acquired knowledge. Afternoon sessions will be project-based: the objective is to, as a group, program a sentiment analysis classifier for Twitter Data, using all the essentials learned during the mornings. By the end of the workshop, participants will be able to read data files, manipulate data using base Python, create and manipulate data frames using Pandas, and run analyses on their data using NumPy and scikit-Learn.


    Prerequisites

    This course has no specific prerequisites.
     
    Software requirements
    Download Anaconda and Jupyter Notebooks. The instructors will provide more detailed instructions beforehand to make sure that all participants have the required software ready before the course begins.


    Schedule

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