Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.


Students are able to recognize the problems of processing data of large scale problems that arise in engineering and computer science. Students can describe the basic theory of such problems, concentrating on results that are useful in computation. Students have a thorough understanding of how such problems are thought of and addressed, and some experience in solving them. Students can apply the methods in their own research work. Students know a number of examples of successful application of the techniques for signal processing of large scale data. More detailed and revised learning outcomes are presented at the beginning of the course.

Credits: 5

Schedule: 11.01.2022 - 16.02.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Visa Koivunen, Esa Ollila, Sergiy Vorobyov

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English


  • valid for whole curriculum period:

    Optimization, subgradient methods, statistical learning.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Lectures, exercises, assignments.

  • valid for whole curriculum period:

    Lectures, excercises approximately 50 h, assignments and independent studying approximately 83 h, total 133 h

    Attendance in some contact teaching may be compulsory.


Substitutes for Courses
SDG: Sustainable Development Goals

    9 Industry, Innovation and Infrastructure


Further Information
  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Spring III-IV

    2021-2022 Spring III-IV

    Course Homepage:

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu ( instead of WebOodi.

    In WebOodi