Basics of AI and machine learning

Artificial intelligence and machine learning are renewing our ways of working. The methods have developed rapidly in recent years, and soon almost anyone will be able to utilise artificial intelligence in their work. However, taking advantage of new opportunities requires knowledge of basic methods.

Machine learning is a specific area of artificial intelligence. Its function is to enhance a software to work better based on ground knowledge and user actions.

During these courses, you will be familiarised with AI and machine learning. Course contents are for example

  • Problem solving using artificial intelligence based approaches
  • Concepts of search, regression, classification and clustering types of problems
  • Difference between supervised and unsupervised learning

You will get a good overview on several intelligent approaches which can be used to solve different types of real life tasks.

NB! Some courses have limits on the amount of FITech students. Persons without a valid study right to a Finnish university have preference to those courses.

AI and machine learning courses:

= Contact learning
= Online learning
= Blended learning (online & contact learning)
Aalto University: Machine learning with Python (CS-EJ3211), 2 ECTS. 9.9.–13.12.2019.

Apply before Sep 2, 2019

Course level: Basic

Language: English

Prerequisites: Basic knowledge of mathematics (functions, vectors and matrices) and basic programming skills in any high-level programming language (e.g. Python).

This course introduces some of the most widely used machine-learning methods such as regression, classification, feature learning and clustering. We will discuss ML in a hands-on fashion using coding assignments, in which we implement ML methods in the Python programming language.

The course is organised in six rounds: introduction, regression, classification, model validation and selection, clustering and dimensionality reduction. Each round covers a certain part of the course book and includes a Python notebook with a coding assignment.

After the course the student understands the basic principles that underlie machine learning. They are able to implement some basic machine learning methods in Python to solve small data science tasks.

For Aalto students: The content of this course overlaps with CS-E3210 Machine learning: basic principles. Both courses cannot be included into degrees.

Responsible teacher: Alex Jung (alex.jung(at)aalto.fi)

Oulun yliopisto: Johdatus tekoälyyn (521160P), 5 ECTS. 9.3.–28.4.2020.

Apply before Mar 2, 2020

Max amount of FITech students: 30

Course level: Basic

Language: Finnish, small part of the course material in English.

No prerequisites, but basics of Python recommended.

Course content:

  • Problem solving using artificial intelligence based approaches.
  • Concepts of search, regression, classification and clustering types of problems.
  • Difference between supervised and unsupervised learning.

The course also covers metrics to measure performance of selected methods.

During the courses the students get a good overview on several intelligent approaches which can be used to solve different types of real life tasks.

The course includes guest presentations on artificial intelligence applications.

More info >> 

Responsible teacher: Olli Silvén (olli.silven(at)oulu.fi)

Further information:

University of Oulu:

Coordinator Riku Hietaniemi (riku.hietaniemi(at)oulu.fi)

Aalto University:

Coordinator Minna Kivihalme (minna.kivihalme(at)aalto.fi)

Contact person, applications:

Pilvi Lempiäinen (pilvi.lempiainen(at)fitech.io)

Type of study unit

Set of courses

Teaching semester

2019–2020

Host university

Aalto University, University of Oulu

Open for degree student

Yes

Open for non-student

Yes

Level of studies

Basic

Teaching methods

Online or contact learning

Place of contact learning

Oulu

Language

English and Finnish

Go back to all Courses & Programs

Go back