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Data Analysis With Python


Admission requirements


Python is a high-level, general-purpose programming language. It is suitable for many applications, ranging from digital humanities to engineering. For instance, most common database structures can be connected to and managed by Python. The language is powerful in GIS applications; users can drastically enhance the capacity of their GIS projects. Artificial Intelligence (AI) is helping us to solve text- or image-related problems. Ultimately, Python offers a good work environment for data analysis.

We use Python to advance our knowledge in statistical computing. Building over the objectives of the Quantitative Methods in Archaeology course, this course introduces key statistical tools and methodologies, such as Analysis of Variance (ANOVA), regression analysis, and non-parametric statistics.
As for computing, the course introduces building blocks of programming, such as conditions and loops. We also learn how to write Python functions assisting in archaeological data analysis.

Course set-up

  • Presentation of course material in a lecture setting;

  • Archaeological data analysis in lab sessions.

Course objectives

  • Learning fundamentals of programming;

  • Gaining coding skills with Python;

  • Applying statistical methods and workflows over a series of univariate and multivariate datasets;

  • Acquiring a computational perspective for archaeological problems.


Course schedule details can be found in MyTimetable.
Log in with your ULCN account, and add this course using the 'Add timetable' button.

Mode of instruction

  • Lectures;

  • Laboratory work.

Assessment method

  • Final project;

  • Assignments;

  • Peer-reviews.

There is one final grade. Passing the average grade is sufficient.

Assessment deadlines

All assessment deadlines (exams, retakes, paper deadlines etc.) can be found in MyTimetable.
Log in with your ULCN account, and add this course using the 'Add timetable' button. To view the assessment deadline(s), make sure to select the course with a code ending in T and/or R.

3 lab assignments are due throughout the block. Assignment peer-reviews follow. The final project is due in the 8th week.

Reading list

Not applicable.


Enrolment through MyStudymap is mandatory.

General information about registration can be found on the Course and Exam Enrolment page.

Exchange and Study Abroad students, please see the Prospective students website for information on how to apply.

All information (costs, registration, entry requirements, etc.) for those who are interested in taking this course as a Contractstudent is on the Contractonderwijs Archeologie webpage (in Dutch).


For more information about this course, please contact dr. T. (Tuna) Kalayci.


  • Attendance is not compulsory but recommended: preparing the final project and solving assignments relies on class participation;

  • Students are expected to work on their own laptop computers in the class. If you do not have access to a computer, please inform the instructor in week 1.