||Linguistics / Taalwetenschappen|
Do you want to become one of the first MSc's in Text Mining? Join one of the last-minute information sessions on the 25th of June!
For mining information from very large repositories of text, you need to know what you are looking for and how to find it. The Master’s programme Text Mining trains everyone with a Bachelor’s and or Master’s degree how to use text mining by applying Artificial Intelligence (AI) techniques. You will learn what the possibilities and limitations are, and how to reflect on the outcomes and the cross-disciplinary aspects.
What is Text Mining?
Did you ever wonder why there is such a need for finding information in text by using Artificial Intelligence techniques? Scientists and decision makers are very much in need of the information that must be somewhere in textual big data. Some examples:
You probably never realized, but most big data is textual and the amount of textual information available in digital form is still rapidly growing. Although language is very accessible for humans, it is not for machines. That massive amount of information is very hard to explore! That is where text mining comes in.
Text mining is trying to extract knowledge, information and structured data from text and utterances by using a collection of software and Artificial Intelligence methodologies. Although text mining is grounded in linguistics, computer science and Artificial Intelligence, it is extremely relevant for almost all fields of knowledge.
As a bachelor or master in your field of knowledge you know what kind of information you could be looking for. With the Master’s programme Text Mining you will become a pioneer in the analysis of textual big data with Artificial Intelligence techniques. You bring your field knowledge, we teach you the tools and techniques.
Text mining is cross-disciplinary in a true sense. There are enough tools available on the internet, but it requires insight, knowledge and experience to use this technology properly for a specific purpose and to understand the outcome. Experts in text mining must have knowledge from both linguistics and technical aspects. Furthermore, they need to understand the field of knowledge in which they are applying these techniques.
In the first period you will learn the basics of linguistics and programming in Python for Text Analysis.
The second period brings you more specialized knowledge and skills: we will show you how to look at language as data and you will learn to use methods and tools for the processing of language in the course NLP Foundations.
In period three and four you will really dive into text mining. In Applied Text Mining we will give you hands-on experience to build what we call a reading machine. In Text Mining in Domains you will apply your newly acquired knowledge in your professional domain. At the same time you will follow a course in Machine Learning, especially for working with language.
You will write your thesis in the last two periods, most likely based on an internship.
For questions on the study programme and courses please contact the study coordinator:
Hennie van der Vliet
T: +31 20 59 86466
Worldwide there is an extremely large amount of digitally available text, yet it is hard to find the right piece of information that is relevant for a specific situation.
There is a fast-growing need for specialists that can apply text mining, turn it into a product and exploit the results in industry, governmental and non-governmental organizations (NGOs).
This Master’s programme offers advanced students a scientific challenge, as well as a great opportunity to apply their field competence in a rapidly growing field of science and industry.
The Master’s programme Text Mining is open for application to students with an academic Bachelor's Degree (or equivalent) in Linguistics.
Students who do not have a Bachelor’s Linguistics degree and wish to enroll for the Master Text Mining are invited to submit a request to the Faculty’s Admissions Board. In response to this request, the Admissions Board will indicate what knowledge, skills and insights the student must have in order to be admitted to the programme.
The knowledge, skills, and insights the student must have in order to be admitted to the programme includes knowledge of linguistic concepts in the fields of phonology, morphology, syntax, semantics and language variation; the ability to observe and analyze phonological, morphological, syntactic and semantic structures in typologically different languages; and insights into the role of linguistics in language therapy, language counselling, language policy and in other social contexts. This knowledge, skills and insights can be acquired in, for instance, a course Introduction to Linguistics of an academic bachelor's programme.
The Faculty’s Admissions Board will review whether you meet the admission requirements.
Dutch students and international candidates with a Dutch degree can apply via Studielink before July 15th for the Master's programme Text Mining under the label Taalwetenschappen (Linguistics).
After you have applied for the master in Studielink, you will receive two emails with your login details for VUnet (VU studentportal). Please complete your application in VUnet . Don’t forget to fill in your specialization on VUnet: Text Mining.
Your application will be reviewed by the Faculty’s Admissions Board. You will be informed whether you have been admitted via Studielink.
English language requirements
Students applying for a Master’s degree programme should be able to speak, read, write and understand English at an advanced academic level.
The proficiency requirement in English can be met by the successful completion of one of the examinations mentioned below, with the scores indicated. Only students who have completed a full high school/International Baccalaureate in English or Bachelor’s degree in Canada, USA, UK, Ireland, New Zealand, or Australia may be exempted.
Please note: tests must have been completed no more than two years before the start of the programme.
See the Admission and language requirements page for further information on the general requirements.
If you have read the admission criteria and feel you are eligible for admission, please take the following steps to submit your application. Note that the initial application procedure is fully online and that scans of your relevant documents are required.
You can find all information on the application procedure on the Admission and Language Requirements page.
Step 1: Meet admission criteria
Step 2: Prepare documents and apply online
Please prepare the following documents. You can find an explanation of each document on the application page. All documents should be provided in English.
After having prepared the required documents, please follow the online application procedure. After you have completed the application, our international student advisors will contact you via email.
Step 3: Await decision on admission
On behalf of the Examinations Board, the Faculty’s Admissions Board will review your application. Normally this takes about four weeks, but it might take longer in busy periods so be sure to apply as soon as possible. If you gain admission, you will receive a letter of conditional admission by email.
Step 4: Finalize your registration and move to Amsterdam!
Make sure to finalize your registration as a student before the start of the programme. On the Admission and Language Requirements page you will find an explanation what to do after admission. When all conditions are met you will be ready to start your programme at VU Amsterdam!
If you are interested in a scholarship, you need to apply for both the Master's programme and the scholarship.
Learn more about Scholarships.
For questions on courses and the study programme
Contact the study coordinator:
Hennie van der Vliet
T: +31 20 59 86466
For practical questions regarding your application, visa, work or other practical concerns
Contact the International Student Advisor:
T: +31 (20) 59 85252
Come meet us at the next Master's Event!
LANGUAGE OF INSTRUCTION
FIELD OF INTEREST
Computer Science, Mathematics and Business
Language and Communication