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Data Science


Disclaimer: in verband met de coronavirus pandemie is deze cursusbeschrijving onder voorbehoud. Voor meer updates over coronavirus, lees nieuws via deze link.

Deze informatie is alleen in het Engels beschikbaar.

Topics: Data Science.
Disciplines: Data science, Life Sciences, Social Sciences.
Skills: Research, presenting, academic writing and reviewing.

Admission requirements:

This course is an Honours Class and therefore in principle only available to students of the Honours College. There are a few places (generally 10-15%) available for second- and third-year regular students. Admission will be based on motivation.


Data Science deals with handling, processing, analysing, interpreting, and extracting knowledge from data, ultimately to derive optimal decisions. Often, the term is associated with the concept of big data, i.e., data that is characterised by large volume, high velocity of generation, and data variety, meaning many different types of information.
Today, data science is of paramount importance in just about any domain, ranging from the life sciences, including e.g. health and biosciences, to banking, sports, insurances, retail, and heavy industries.
The possibilities for generating new insights and decisions based on data are considerable. This Honours Class first introduces students to some of the fundamental concepts and tools of Data Science, an introduction into Python programming for data analysis and then continues with overviews of specific applications.

Course objectives:

Upon successful completion of this course, students will:

  • Have a general overview of the possibilities in the field of data science;

  • Have knowledge of different types of data;

  • Be able to understand and perform basic data analysis tasks using Python;

  • Have basic knowledge of some of the tools used in data science;

  • Have developed skills for several tools for analysing data;

  • Have experience with performing basic analyses for real-world applications.

Programme and timetable:

This course will take place on Mondays from 17:00-19:00, starting in February 2022.

Lecture 1: February 7
Introduction to data science - Python practical: set-up.

Lecture 2: February 14
Supervised learning models: classification - Python practical: introduction to Python and import data.

Lecture 3: February 21
Supervised learning models: regression - Python practical: exploratory data analysis.

Lecture 4: February 28
Unsupervised learning models - Python practical: exploratory data analysis.

Lecture 5: March 7
Tools and model evaluation - Python practical: Model fitting.

Lecture 6: March 14
Data science in society - Python practical: Model fitting.

Lecture 7: March 21
Guest lectures on specific data science applications.

Lecture 8: March 28
Guest lectures on specific data science applications.

Lecture 9: April 4
Guest lectures on specific data science applications.

Lecture 10: April 11
Guest lectures on specific data science applications.

Lecture 11: April 18
Final seminar with student presentations and discussions.

Old Observatory, room C003

Reading list:

Course load and teaching method:

This course is worth 5 ECTS, which means the total course load equals 140 hours:

  • Lectures: 6 of 1 hour, 4 of 2 hours (participation mandatory

  • Practical sessions: 6 of 1 hour (participation mandatory

  • Preparation lectures: 1 hour/week

  • Preparation practical and practical assignment: 5 hours/week

  • Final group assignment and seminar: 60 hours

Assessment methods:

The assessment methods will look as follows:

20% presentation (5 minutes) during final seminar;
50% paper (3000 words);
20% practical assignment;
10% participation (active).

Brightspace and uSis:

Brightspace will be used in this course. Upon admission students will be enrolled in Brightspace by the teaching administration.

Please note: students are not required to register through uSis for the Bachelor Honours Classes. Your registration will be done centrally.

Registration process:

Submitting an application for this course is possible from Monday 1 November 2021 up to and including Thursday 11 November 2021 23:59 through the link on the Honours Academy student website.

Note: students don’t have to register for the Bachelor Honours Classes in uSis. The registration is done centrally before the start of the class.

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