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Deep Learning in Data Science

Data science is an interdisciplinary field, using skills and methods from computer science, mathematics and statistics to extract knowledge from (large) data sets.

Information for admitted students Spring 2021

Congratulations! You have been admitted at Stockholm University and we hope that you will enjoy your studies with us.

In order to ensure that your studies begin as smoothly as possible we have compiled a short checklist for the beginning of the semester.

Follow the instructions on wether you have to reply to your offer or not.
universityadmissions.se

 

Checklist for admitted students

  1. Activate your university account

    The first step in being able to register and gain access to all the university's IT services.

  2. Register at your department

    Registration can be done in different ways. Read the instructions from your department below.

  3. Read all the information on this page

    Here you will find what you need to know before your course or programme starts.

IMPORTANT

Your seat may be withdrawn if you do not register according to the instructions provided by your department.

Information from your department

On this page you will shortly find information on registration, learning platform, etc.

Welcome activities

Stockholm University organises a series of welcome activities that stretch over a few weeks at the beginning of each semester. The programme is voluntary (attendance is optional) and includes Arrival Service at the airport and an Orientation Day, see more details about these events below.
Your department may also organise activities for welcoming international students. More information will be provided by your specific department. 

su.se/welcomeactivities 


Find your way on campus

Stockholm University's main campus is in the Frescati area, north of the city centre. While most of our departments and offices are located here, there are also campus areas in other parts of the city.

Find your way on campus


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New student

During your studies

Student unions


For new international students

Pre-departure information

New in Sweden

You will learn to

  • explain the basic the ideas behind learning, representation, and recognition of raw data,
  • account for the theoretical background for the methods for deep learning that are most common in practical contexts,
  • identify the practical applications in different fields of data science where methods for deep learning can be efficient (with special focus on computer vision and language technology).

Only students from the following programmes can apply: Master's Programme in Mathematical Statistics, Master's Programme in Actuarial Mathematics, and Bachelor's Programme in Computer Science.

This course is given jointly with KTH, and you can find more information about the schedule, course literature etc. on KTH's pages - see links below.

  • Course structure

    The course consists of two elements; practical exercises and theory.

    Teaching format

    The education consists of lectures.

    Assessment

    The course is assessed through a take-home exam, and written presentation of the practical exercises. For information on how to register for exams at KTH, see:

    Exam information

    Examiner

    A list of examiners can be found on

    Exam information

  • Schedule

    The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.

    Schedule for DD2424 at KTH

  • Course literature

    Note that the course literature can be changed up to two months before the start of the course.

    See course information for DA2424 at KTH

  • More information

    New student
    During your studies

    Course web

    Registered students get access to the KTH course web in Canvas.

  • Contact