Here you can find a summary of all the useful information that you need as a new student.
You can find also more detailed the information in the A-Z list.
The Introduction Day for new students starting in September 2019 will be held on the 29th of August.
Please keep in mind that attendance at the Introduction Day is compulsory. If you are unable to attend please contact the study advisor Janine de Schutter: email@example.com
Introduction Day programme:
|13.00-13.30||Doors open, registration, coffee/tea in Central Entrance Hall|
|13.30-14.15||Tour of the Campus|
Welcome to all new Master students of the 2-year Master's Programmes
|15.00-16.30|| Programme per Master: Introduction to the programme by the Programme Director/ lecturers/ students
|16.30-21.00||Reception with drinks and snacks for all new Master students of the Graduate School of Informatics|
As a student of the joint degree Computational Science you are invited to join the Introduction Day of the VU on Wednesday August 28th, starting at 1pm in WN-S010 (Student Association Storm).
Attendance at the Introduction day at the VU is not compulsory for students of the joint degree master programme Computational Science. However, it does provide joint degree students the opportunity to see the campus and get acquainted with the VU students.
Programme Introduction Day VU:
|Meeting point before the start of the faculty introduction||Storm's room: WN-S010|
|13.15-14.15||VUnet instructions (optional)||WN-S201, WN-S203, WN-S205|
|14.15-15.15||Campus Tour by study association STORM (optional)||Starting point: Storm's room WN-S010|
|15.15-15.45||General welcome by coordinator, FSR and study association||WN-KC159|
|16.00-16.30|| Introduction per master:
Computer Science +PDCS- Wan Fokkink
|16.30-18.30||Drinks and welcome by the dean Prof. dr. Guus Schreiber||Tuinzaal (WN-VOO2)|
With your UvA-net ID you can register for courses via https://datanose.nl/#masterenrol.
Once you have registered here, you will automatically be enrolled for the compulsory courses in the first semester.
Within the Computational Science (CLS) curriculum, three courses (in total 18 EC) in the first semester are compulsory. In principle, that would leave you with 12 EC (2 courses) to choose from. Please consult the Course Catalogue for information on courses (see below). During the Master Introduction, detailed information on constrained choice courses and (recommended) elective courses will be given as well.
As your situation is different from that of the other first-year students, please follow this link to enrol for UvA courses in the first semester: https://datanose.nl/#specialenrol. Mention your status as ITMO student in the form.
To register for the courses in the second semester, you have to do this yourself through SIS, see: http://student.uva.nl/sis/
Please note that the deadline for registration for courses of the 2nd semester is in December 2019 or January 2020. You will be informed about this through email.
Due to the large number of students who applied for admission to the master programme AI this year, the courses of the master programme AI face huge capacity problems. Therefore, the programme was forced to place some restrictions on several courses. The programme and the Graduate School of Informatics regret having to enforce these restrictions on courses, but lacks the facilities to admit all students from other programmes.
Machine Learning 1, Knowledge Representation, Computer Vision 1, Information Retrieval 1, Natural Language Processing 1 and Multi-Agent Systems. These are 6 of the 7 core, mandatory courses of the master programme Artificial Intelligence and due to the limited capacity only students from the master programme Artificial Intelligence will be admitted to these courses. As an exception to this rule: students who failed the course last year will be admitted to the course in order to do a resit exam.
Other students can request registration for a course here: https://datanose.nl/#specialenrol or by sending an e-mail to firstname.lastname@example.org. This applies to the following courses: Deep Learning, Knowledge Representation on the Web, Natural Language Processing 2, Statistical Methods for Natural Language Semantics, Deep Learning for Natural Language Technology, Information Retrieval 2, Information Visualization, Machine Learning for Natural Language Processing, Probabilistic Robotics, Reinforcement Learning, Seminar Combining Symbolic and Statistical Methods in AI.
Consult the Course Catalogue for general educational information and for specific information about the master’s programmes, courses, contact persons, etc. The Course Catalogue is available online.
All students of the master Computational Science are expected to use their own laptop.
As soon as you are enrolled as a student at the UvA you will receive a UvAnetID from the Central Registration Office. If you completed your bachelor study at the UvA, your UvAnetID is still the same. If you have any problems with your UvAnetID password, you can contact the Education Desk at Science Park 904 for assistance.
You will need a student ID card to identify yourself for classes, exams and study centres at all UvA locations, and to borrow books at the University Library (UB).
UvA students can use an UvA email address via Google Apps for Education.
Most UvA-courses are supported by Canvas, our online learning environment. login with your UvA-net ID.
In October, The Faculty of Science will organize a special event for all its international students. You will get acquainted with the Dutch academic environment, receive information about social activities and meet the other international students during drinks and pizza.
We hope to see you all there! In September you will receive an invitation with more details for this event by email.
Students may consult the study adviser for advice on individual situations like studying with a disability/chronic illness, combination study/work, personal circumstances, (temporarily) terminating the study programme as well as for advice regarding planning or doubts about your master’s programme. The study adviser can refer to lecturers, committees and departments within or outside the Faculty. The study adviser has knowledge of the rules and regulations concerning the educational system.
The Education Desk is situated at Science Park 904 on the first floor. Opening hours daily from 9.00 am to 5.00 pm.
Master students primarily contact the Education Service Centre for:
Please contact the Education Desk FNWI.