RSS001.O2 Introduction to Programming in Python​

This Python course is designed especially for social scientists who have limited or no programming experience. Therefore, the course focuses on hands-on exercises and practical tips to help you start your journey in the world of Python. To keep classes interactive, each class requires preparation – such as watching videos that explain theory and methods, going through code, and tiny exercises.

Day 1 Introduction to Python and Jupyter Notebook 
Learn how to operate Jupyter Notebooks, through Google Colab. We also cover different data types in Python, loops, and conditions.

Day 2 Learn Python the fun way 
Practice, practice and practice! Bunch of fun coding games to master the syntax and learn to collaborate in teams.

Day 3 Data collection I – Web scraping 
Python is a popular language to extract data from the internet. Learn how to extract data from semi-structured websites and save the results into .xlsx and .csv files.

Day 4 Data collection II – AP
Most social media sites such as Facebook and Twitter, and Wikipedia, allow scientists to collect publicly available data from their services through Application Programming Interfaces: APIs. Learn how to use APIs, (understanding the documentation, parsing json files), and collect and save data different APIs.

Day 5 Data Analysis I– Data analysis with pandas and introduction to data visualisation 
We introduce the basic data analysis toolkit of Python (Pandas, Matplotlib, Seaborn). You will work in groups to analyse a pre-defined database, then present your findings to the class.

How will the course work online? Introductory pre-recorded videos and required readings (mainly documentation of the libraries) will help you prepare for classes. The first 2 hours of each class will focus on introducing new materials, then after the lunch break you will code, either alone or in groups, with live support from the instructor and Teaching Assistant.

Dates

12 June 2023 - 16 June 2023
Course Fee

Regular: €560
Students & PhD's: €395

Early Bird Regular: €504 (application deadline* April 1st) 
Early Bird Students & PhD's: €355,50 (application deadline* April 1st)

Scholarships and discounts

Please note that Erasmus+ scholarships are not possible for this course

Find more information here

Application deadline

May 1st

*Your application is only completed when the course fee has been paid

Course leader Orsolya Vásárhelyi
Level of participant
  • Master
  • PhD
  • PostDoc
  • Professional
Admission requirements ​There are no requirements for this course
Admission documents
  • ​To get the student/PhD discount you need to upload a copy of your Student card or other proof of registration
  • If you are not a student/PhD, you can upload an empty document under 'Student Card'.
Mode of Study Online
ECTS 1
Location Online