Basics of AI and machine learning
AI and machine learning courses:
Application period has ended.
Course code: CS-EJ3211
Course level: Basic
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)
Apply before Mar 2, 2020
Course code: 521160P
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.
- 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.
Responsible teacher: Olli Silvén (olli.silven(at)oulu.fi)
University of Oulu:
Coordinator Riku Hietaniemi (riku.hietaniemi(at)oulu.fi)
Coordinator Minna Kivihalme (minna.kivihalme(at)aalto.fi)
Contact person, applications:
Pilvi Lempiäinen (pilvi.lempiainen(at)fitech.io)