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Python for Absolute Beginners pt. 2

Python for Absolute Beginners pt. 2 In-Person

Note: This is part 2 of 2. For registration to part 1, visit here:
or here:

This course is intended for students who have never tried programming before and want to build their skills in Python from the bottom up.

Intimidated by mathematics, numbers, and obscure Python scripts? Don’t be! We will be covering all the very basic concepts and building blocks in order to get complete beginners, who have no experience writing code, working in Python.

This will include explaining the concepts of variables and data types, as well generating some basic scripts to interact with these data, such as lists, loops, and conditionals. By the end of this course, you will have an understanding of the basic building blocks in Python. You will also come away with an appreciation for how a computer program “thinks”. All we require from you is a will to learn. We look forward to seeing you!

The course is divided in two parts. The first covers different datatypes in Python and how data is stored. In other words, it is an introduction to the building blocks of coding in Python.

The second part expands on this by putting these blocks together to create simple scripts. If you already have some understanding of Python, feel free to skip the first section. Otherwise, we recommend that you start with pt. 1 and then move on to pt. 2.


Practical information: We will be working in Jupyter Lab / Jupyter Notebook, which requires some installation, but you can also work in either Google Colabs or ERDA which require only a Google or KU account, respectively. For more information and help, consult the course page:


As written, this course is an introduction to the basics of Python. If you have never programmed before, this is a good place to start before you move on to some of our more advanced courses:




Related LibGuide: KUB Datalab by Christian Knudsen

9:00 - 12:30
Time Zone:
Central European Time (change)
KUB Datalab - Samf
SAMF: Det Samfundsvidenskabelige Fakultetsbibliotek, Gothersgade 140, 1123 København K
  Analysis     Datalab     English  
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Event Organizer

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Benjamin Derksen
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Nynne Overlund
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Daniel Pryn