Data analytics

Have you heard the quote “Data is the new oil”? Sounds right, but it might not actually be true. For many companies data is certainly more valuable than oil, but making business out of data is complicated. You need advanced skills to process and analyse data. These courses teach you how to do it!

NB! These courses have a limit on the amount of FITech students. Persons without a valid study right to a Finnish university have preference to the course if not mentioned otherwise.

Data analytics courses:

= Contact learning
= Online learning
= Blended learning (online & contact learning)
LUT University: Digital signal processing, 4 ECTS. 2.9.–13.12.2019.

Application period has ended.

Course code: BL40A0401

The course is not available for degree students!

Max amount of FITech students: 20

Course level: Basic

Language: Finnish

Prerequisites: Basics of complex arithmetic, basics of series calculation, theory of continuous-time signals.

Signal processing skills are important when practical industrial applications are considered.

Course content:

  • Principles of sampling
  • Discrete-time signals and systems
  • z-transform and its application to the analysis of linear time-variant systems
  • Frequency analysis of signals and systems
  • Discrete Fourier transform (DFT)

The course acquaints the student with fundamentals of digital signal processing. Upon completion of the course the student will be able to:

  1. analyse discrete-time systems in time, z- and frequency domain
  2. design simple digital filters by using pole-zero placement
  3. apply the discrete Fourier transform (DFT) to signal analysis and explain how it is related to other transform methods.

Responsible teacher: Antti Kosonen (antti.kosonen(at)

More info >>

LUT University: Measurement technology, 5 ECTS. 2.9.–13.12.2019 & 7.1.–17.4.2020.

Application period for 1st course has ended. For the 2nd course, apply before Dec 16, 2019.

Course code: BL40A0100

Course level: Basic

Prerequisites: Basic mathematical skills.

The course focuses on measurement systems and introduces method to analyse the measurements.

Upon completion of the course a student will be able to:

  1. apply fundamentals of measurement
  2. apply analog and digital signal conversions
  3. apply digital signal filtering and data transfer
  4. apply IoT applications of digital signal manipulation.

More info on LUT University’s WebOodi page.

Responsible teacher: Niko Nevaranta (niko.nevaranta(at)

Aalto University: Data science, 5 ECTS. 28.10.–16.12.2019.

Apply before Oct 21, 2019

Course code: CS-C3160

Max amount of FITech students: 100

Course level: Advanced

Language: English

Prerequisites: Skills needed on the course are taught on introductory courses in mathematics, statistics and programming. Specifically, matrix algebra, derivatives of functions and statistical distributions will be needed on this course.

The course serves as an introduction to the topic of data science and related topics such as machine learning. You will be introduced to data science methods and tools to find interesting information from data.

Specific topics on the course include

  • processing of digital signals such as speech and images
  • statistical estimation of parametric distributions
  • classification
  • prediction
  • clustering
  • pattern mining
  • network analysis for developing search engines for hypertext collections such as the web.

After the course, you can describe how natural data such as images, natural language, speech and time series measurements can be represented as data in digital form. You can apply elementary statistical and algorithmic methods to process the digital data to yield insights to the data generating phenomenon. You will understand what processes constitute the data science pipeline in the analysis, starting from natural data and ending with actionable results.

More information on Aalto Unversity’s WebOodi page.

Responsible teacher: Jaakko Hollmen (jaakko.hollmen(at)

University of Turku: Acquisition and analysis of biosignals, 5 ECTS. 29.10.–18.12.2019.

Apply before Oct 16, 2019

Course code: DTEK0042

Course level: Advanced

Language: English

Prerequisites: Basics of digital signal processing recommended but not required.

Course content:

Review of different physiological signals such as heart rate, body and skin temperature, blood pressure, oxygen saturation and respiration rate etc. which can be monitored by wearables. What kind of sensor technology is required to capture each of these physiological signals. Signal conditioning and processing for different types of biosignals; for example electrocardiography (ECG), electroencephalogram (EEG), electromyography (EMG) all measure electrical signals from the body, but have different applications and different signal processing.

After completing the course teh student should

  • understand how the sensor technology and information technology can be exploited in the healthcare sector
  • learn principles of signal processing methods for biosignals and the limitations imposed by wireless hardware.

Responsible teacher: Mikko Pänkäälä (mikko.pankaala(at)

More info on University of Turku’s study guide.

University of Turku: Data analysis and knowledge discovery, 5 ECTS. 29.10.–18.12.2019.

Apply before Oct 21, 2019

Course code: TKO_3103

Course level: Advanced

Language: English

The course introduces methods and algorithms for extracting information and knowledge from datasets. This includes techniques for visualisation, classification, regression, outlier detection, rule induction, model complexity selection, and model validation.

This course enables students to learn when and how to apply state of the art data analysis and knowledge discovery tools for data. Students will learn modern data analysis methods and algorithms to discover patterns and trends in large, complex and high-dimensional data sets, and turn data into information and knowledge.

Responsible teacher: Antti Airola (antti.airola(at)

More info on University of Turku’s study guide.

University of Oulu: Big data processing and applications, 5 ECTS. 9.3.–5.5.2020.

Apply before Mar 2, 2020

Course code: 521283S

Max amount of FITech students: 30

Course level: Advanced

Language: English

Prerequisites: BSc in Computer science or equivalent.

During this course, the student gets familiar with the concept of “big data” and different phenomena related to it, including requirements and principles for data intensive systems and their implementation as well as benefits, risks and restrictions of available big data solutions.

The course includes invited lectures from industry.

After the course the student can identify real life cases where big data solutions are needed and design basic solutions to big data problems.

More info >>

Responsible teacher: Ekaterina Gilman (ekaterina.gilman(at)

Further information:

Aalto University

Minna Kivihalme (minna.kivihalme(at)

LUT University

Uolevi Nikula (uolevi.nikula(at)

University of Oulu

Riku Hietaniemi (riku.hietaniemi(at)

University of Turku

Timo Vasankari (timo.vasankari(at)

Contact person, applications:

Pilvi Lempiäinen (pilvi.lempiainen(at)

Type of study unit

Set of courses

Teaching semester


Host university

Aalto University, LUT University, University of Oulu, University of Turku

Open for degree student


Open for non-student


Level of studies

Basics and advanced

Teaching methods

Online or contact learning

Place of contact learning

Oulu, Turku


Finnish & English

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