Are you interested in the growing field of data analytics, and would you like to further develop your skills in this field? Then this minor could be something for you!
Historically, all empirical sciences, from the natural sciences to the social sciences and humanities, have used data. Recently, however, scientific data’s sheer volume, velocity, and variety, as well as the power of computers and methodology to generate scientific knowledge from the data, have started increasing drastically and in fact are expected to remain increasing over the coming decades.
Commensurately with this growing availability of data, data-analytic tools and computer capabilities, research questions across fields are becoming more complex, leading to commonalities in addressing problems encountered across a large number of fields represented at UU. This similarity of structure of apparently different problems is rapidly leading to the development of a new scientific field to deal with these problems regardless of object of research. This new field is called ‘Applied Data Science’. In Utrecht University it is one of the seven focus areas.
In this Minor you will be introduced to this field. There will be much emphasis on the analysis of data (and the fun of this!), and you will be introduced to programming.
In the courses you learn how to analyse data in a “data science” way. Here prediction and visualization play a central role. Data sets will be derived from different fields, and realistic questions will be asked about these data.
Data are everywhere but they are not always in the right format to analyse them immediately. Therefore, in the courses we also offer you tools to handle the data and write (simple) programmes to manipulate the data.
Software used is, among others, R and Python. These are programming environments that are free of charge and that are most popular in the field of (applied) data science.
This Minor is intended for students who find it interesting to answer questions by analysing data. It is offered to all students of Utrecht University, so it is likely that during this Minor you will be part of a diverse community of students coming from different fields, such as the social and behavioural sciences, the humanities, geosciences, health and sciences.
All students can enter this Minor.
For the block 2 course Fundamental techniques in data science with R, the required entrance level is familiarity with correlation and regression, comparing means and cross tabulations of categorical variables. We also expect that you have hands on experience in carrying out these analyses with, for example, SPSS, Stata, R or SAS.
It is possible that you do not have the right entrance level. In that case, you will obtain the appropriate level by following this course in block 1 (taught in Dutch):
|201900025||Basis van Onderzoeksmethoden en Statistiek||1||1||Dr. Peter Lugtig|
When you have followed an introductory statistics course of 7.5 EC, we expect that you will have the required entrance level. When you are in doubt about this, please contact Gerko Vink (email@example.com) who is the teacher of the obligatory course in block 2.
The Minor consists of four courses, where two courses are obligatory for everyone. The other two can be chosen, depending on the bachelor programme you are following.
The obligatory courses are:
|201900026||Fundamental techniques in data science with R||2||2||Dr. Gerko Vink|
|201900027||Applied data analysis and visualization||4||3||Dr. Emmeke Aarts|
In these two courses you learn how to analyse data. The approach of data analysis in statistics is different from the approach of data analysis in data science, and we will teach you the latter. For example, there is more attention for prediction of an outcome, and less for statistical significance.
Programming and further data handling is also an integral part of data science, as data are often not yet in the format that you can analyse them. For this we offer the following course:
|INFOB2PWD||Programming with data||3||2||Dr. Anna-Lena Lamprecht|
This course is not obligatory but highly recommended. When you are interested in following the Master Applied Data Science though, it is important to know that this course is an entrance requirement for this Master.
There are a number of other courses that can be chosen so that in the end the total number of courses followed is four. The following additional courses are offered:
|201800138||Measurement and modelling with social data||2||3||English||Dr. Wojtek Przepiorka, dept. of sociology|
|200300125||Theory Construction and Statistical Modelling||1||3||English||Dr. C. Van Lissa, dept. of methodology and statistics|
|201500130||Missing Data Theory and Causal Effects||3||3||English||Dr. G. Vink, dept. of methodology and statistics|
|BMW33316||Bioinformatics and genomics*||4||3||Dutch, or English when there are exchange students||Prof. dr. Berend Snel, biomedical sciences|
|INFOB2KI||Kunstmatige intelligentie||2||2||Dutch||Dr. S. Renooij, dept. of information and computing sciences|
|INFOB2DA||Data analytics||2||2||English||Dr. Marco Spruit, dept. of information and computing sciences|
|INFODB||Databases||3||2||Dutch||Drs. H. Philippi, dept. of information and computing sciences|
|GEO2-4208||Aardobservatie en data analyse||3||2||Dutch||Dr T. de Haas, dept. of physical geography|
|GEO3-4308||Hands on GIS||Offered in both 2 and 3||3||English||Drs. M. Zeylmans van Emmichoven, dept. of physical geography|
|GEO2-3031||Introductie GIS / Cartografie||Offered in both 2 and 3||3||English (block 3), Dutch (block 2)||Drs. F. Toppen, dept of human geography and planning|
|GEO3-3024||Advanced GIS||Offered in both 2 and 3||3||English||Dr. S. Scheider, dept of human geography and planning|
Please note that some courses have entry requirements that you need to uphold. Please look closely at the course texts and when in doubt, contact the course coordinator/ADS contact person.
Since these courses are offered by different faculties, please also pay attention to the registration periods per course as they can differ per faculty.
*Should you be interested in the Bio informatics course offered in block 4, know that you cannot register via OSIRIS Student. Instead, send an email to BachelorBMW@umcutrecht.nl.
Students are free to choose additional courses in any of the blocks.
Given that your previous education is sufficient to start with the course Fundamental techniques in data science with R, a possible set up of this minor would be:
|Block 1||Block 2||Block 3||Block 4|
|(additional course, for example Theory construction and modelling)||Fundamental techniques in data science with R||(Programming with data or another additional course, for instance Databases)||Applied data analysis and visualization|
Should your previous education not suffice to start with the course Fundamental techniques in data science with R, a possible set up of this minor would be:
|Block 1||Block 2||Block 3||Block 4|
|Basis van Onderzoeksmethoden en Statistiek||Fundamental techniques in data science with R||(Programming with data or another additional course, for instance Databases)||Applied data analysis and visualization|
There is a maximum of 70 participants per year for this minor.
Utrecht University students
Register via OSIRIS Student. Enrolment is in order of registration. When the maximum number of students has been reached, the registration will close. We advise to register yourself for the minor first to see whether there is still room left, and then register for the separate courses. Also pay attention to the registration periods as they may differ per faculty.
Students outside of Utrecht University
Enrol for the courses through our application form at OSIRIS Online Application (visit our subsidiary courses page for more information). Use the same application form to apply for the minor. Given that the maximum number of participants has not yet been reached, the Student Information Point will process your form and enrol you for the minor.
When you have passed all courses in a minor, you can apply for a minor declaration.
Check the Frequently Asked Questions (pdf) about this minor.