Practical information

About the course

This course is a hands-on practical introduction with no prerequisites in applying computer science techniques (like programming and machine learning) in humanities and social science research. It will cover a broad range of techniques and methods representing the latest methodological innovations in social science and humanities applications of machine learning and artificial intelligence.

The course is meant as a hands-on tools workshop focusing on the practical application of these methods and will not go in depth with the mathematical and theoretical foundations. It will rather provide a broad overview of the data science ecosystem and toolbox. We do not expect you to be able to immediately implement the methods in your own research, but the course should provide a good jumping-off point for starting to integrate these methods.

Teaching format

Interactive notebooks and live coding

Teaching consists of a mixture of lectures and exercises using interactive online notebooks on Google Colab allowing you to try out and use the various methods as they are being taught. Exercises consist of both live coding and adapting code to solve specific problems or create specific outputs.

Portfolio work

Each day you are given an hour to work on a portfolio with the possibility of sparring with the course lecturers. Here you are expected to solve a limited number of problems using the methods and tools taught during the given day by writing your own code in a notebook.

At the end of the week, you are expected to hand in your combined portfolio (the notebook containing all your code) in order to receive credits.

Meals

Breakfast and lunch for the whole week is included in the course.

• Breakfast is served every morning in the classroom from 8.30-9.00.

• Lunch is served in the CREATE canteen every day from 12.00-13.00.

If you have any dietary restrictions, please contact the course organizer Kristian Gade Kjelmann (kgk@adm.aau.dk) as soon as possible.

Social gathering on Wednesday Nov. 27th

We (the course organizers and lecturers) would like to invite all interested participants to join us for a dining and social event.

The event will take place on Wednesday Nov. 27 from 18:30-22:30 at Restaurant Pingvin. Dinner and accompanying drinks are covered by the course (any further drinks you will have to pay for yourselves).

Sign up by filling out this registration form: http://bit.ly/sdsphd19social

We hope to see as many of you as possible!