Studies

Subprogramme of Algorithms, Data Analytics and Machine Learning

Degree requirements

 

Recent changes

The degree requirements of the subprogramme were changed in Autumn 2014, at which time the name of the subprogramme was changed from Algorithms and Machine Learning to its current form Algorithms, Data Analytics and Machine Learning. This page describes the current degree requirements. The previous requirement are recorded on a separate page. At the bottom of the page there is a summary of the changes. In practice the main effect to actual studies should be that there are a little more options for elective courses.

Starting in Autumn 2014, we are also offering a special study profile in Data Science. The profile combines studies from subprogrammes Algorithms, Data Analytics and Machine Learning and Networking and Services to give the student a good understanding of concepts and tools needed in analysing very large data sets often in a highly distributed environments. Details are given below.

For any questions regarding the degree requirements, please contact the study advisor Tomi Pasanen or the head of the subprogramme Jyrki Kivinen.

 

Bachelor of Science

Practically all courses leading to a bachelor's degree are taught in Finnish. International students are expected to have a suitable bachelor's degree from some other institution, based on which they may be accepted to study directly for a master's degree. However some master's students may find it useful to strengthen their prerequisite skills by including some bachelor's level courses in their studies. In particular, the courses Models of computation and Operating Systems are considered essential for all master's students at our department and are therefore recommended for students who do not have a corresponding course in their bachelor's studies.  Although the courses are lectured in Finnish, there is often at least an exercise group in English.

 

Master of Science

Beginning from Autumn 2010, all compulsory courses and most of the special courses of the specialisation area are lectured in English. However some special courses may be offered only in Finnish.

To complete the Master's degree requirement, the student must complete both some general studies, and the advanced module in computer science. Additionally the degree usually includes some minor subjects.

General studies

The requirements for general studies are the same for all subprogrammes. They are described on their own page.

Advanced studies in computer science (algorithms, data analytics and machine learning)

Compulsory courses of the subprogramme (10 cr)

Elective courses of the subprogramme (24 cr)
  • at least 10 cr of the following:
    • String processing algorithms
    • Probabilistic models
    • Data mining
    • Data Compression Techniques
    • Randomized Algorithms
    • Approximation Algorithms
    • Information Theoretic Modelling
    • Supervised Machine Learning (no longer offerred)
    • Unsupervised Machine Learning (no longer offerred)
    • Course in Advanced Machine Learning (replaces Supervised and Unsupervised Machine Learning)
    • Introduction to Computational Creativity
    • Any project work directly related to these courses
  • 14 cr of advanced studies in computer science as specified in a personal study plan (FM-HOPS) approved by the department
Seminars (6 cr)
 
Master's thesis and maturity exam (40 cr)

Minor subjects

Studies in the subprogramme require certain mathematical skills from the beginning. Students are strongly recommended to include a total of at least 60 cr of mathematics and statistics in their bachelor's and master's degree, and it would be most useful if of this is already taken care in bachelor's studies. In particular, basic courses in real analysis, linear algebra, mathematical logic and probability and statistics are useful.

Other recommended minor subjects include physics, theoretical physics, statistics, language technology and cognitive science. It is also possible to take courses in other Finnish universities based on the JOO Flexible Study Rights Agreement.

Other studies

The requirements for other studies are the same in all subprogrammes.

  • 582510 Personal study plan (FM-HOPS) (1 cr)
  • 582519 Scientific Writing for MSc in Computer Science, if the student begins his or her studies at the department directly at Master's level and will complete the degree in English (3 cr)
  • 581324 Computing Tools for CS Studies, if the student begins his or her studies at the department directly at Master's level (1 cr)
  • English language studies as specified in the approved personal study plan (0–4 cr)
  • 584403 Advanced Internship or Vocational Orientation Studies (at least one of the following) (min. 2 cr)
    • 582511 Advanced professional IT working (2–6 cr) or
    • 581387 Software Factory Work Experience (5–7 cr) or
    • 582515 Information Technology as a Profession (2 cr) or
    • 582613 Advanced Internship in Bioinformatics (1–3 cr)
  • optional courses so that the extent of the degree, 120 credits, is fulfilled (may include major or minor subject courses or courses in other subjects)

 

Data Science

A special Data Science study profile educates students on the challenges of big data, both from a system viewpoint and an algorithmic, data analytical viewpoint. The profile is offered together by the Algorithms, Data Analytics and Machine Learning subprogramme and the Networking and Services subprogramme.

For students in the Algorithms, Data Analytics and Machine Learning subprogramme, the Data Science study profile has the following additional requirements.

  • Additional obligatory course: Distributed Systems (5 cr)
  • “At least one of these” of Algorithms, Data Analytics and Machin Learning subprogramme requirements above is replaced by elective courses as indicated on the Data Science study profile page

 

Changes to degree requirements starting Autumn 2014

Students who started their studies in Autumn 2014 study according the new degree requirements described here. Students who started earlier can study according to either the new requirements or the older requirements that were valid when they started. There is no need to formally change to the new requirements, one simply needs to plan ones studies so that one set of requirements becomes fulfilled. In practice, the difference in the old and new requirements should have little or no effect to the studies of most students. The main changes are the following:

  • The courses Design and analysis of algorithms and Introduction to machine learning are now 5 cr instead of 4 cr. This reflects an increase in lecture hours and the observation that the courses have been percieved as demanding. The old 4 cr versions can be used also with the new degree requirements, as long as the total number of credits in the advanced module is at least 120.
  • There is now more flexibility in choosing the elective courses.
  • We have removed the requirement for a combined 60 cr of mathematics or statistics in Bachelor's and Master's degrees. Mathematics and statistics are still extremely important supporting subjects and we strongly recommend that you study at least 60 cr of them. This change just means that we will not formally count how much you have in your Bachelor's degree.
  • It is now a formal requirement that the elective courses must follow an approved study plan. This is of course what everyone should have been already doing anyway.