In this course students learn the basics of computer architecture, programming, algorithmic thinking and the Python language. After finishing this course you will:|
- be able to analyse simple problems and break them down into steps that a computer can execute
- have a basic knowledge of Python allowing you to further develop these skills by applying them in other courses and projects
Programming skills are becoming an important part of the scientific toolbox. Many linguistic studies contain more data than is feasible to edit and process by hand and machine learning is rapidly improving on many tasks like translation, parsing and speech recognition. While there are user friendly software kits like SPSS, the best thing about programming is not being limited to tools that already exist. Being able to write your own scripts and adapt those of your fellow scientist is much more flexible and powerful.|
Python is one of the most widely used programming languages in both science and industry. It is so popular because it is open source (it is free and anyone can add/edit/improve whatever they need) and because it is available on many operating systems.
In this course we take plenty of time to explain the basics of python and will not deal with more complex concepts such as classes. In this course you will learn first how a computer works, what its basic components are, followed by the basics of Python programming and algorithmic thinking: the process of converting the problem or task you want to solve into clear steps that can be executed by your computer. The course consists of lectures combined with weekly lab sessions and assignments to put the lecture into practice. The material and assignments will focus on skills that are relevant for linguistic/language technology research such as processing text and experimental data and using Python to analyse your data.
Only accessible to:|
- students without any programming experience
- students CIW: B2 major elective course
- TW students: B2 major elective (entrance requirement for B3 internship at CLST)
- minor Data & Society (interdisciplinary package, see appendix): this minor is open to ALL Arts students
- minor in Data Science, where this course is only intended for students of Arts, FFTR, and Law.
Not recommended. If you know how a variable is used, this course might be too easy for you.
You must attend the lectures and the practical sessions to pass.
- You must use your own laptop for this course.
- This course is only open to students who are enrolled in a bachelor of the Faculty of Arts (Letteren), a bachelor of the Faculty of Philosophy, Theology and Religious studies (FTR) or a bachelor programme of the Faculty of Law (Rechtsgeleerdheid).