Machine Learning (OPEN UNI)

After completing the course, student 1. can design and implement basic machine learning algorithms for regression and classification applications. 2. can design and implement methods for optimizing cost functions for machine learning tasks. 3. can apply the most common methods for machine learning.

Lectures 16 h, Fully guided working on assignments 4 h, Independent working on assignments 100 h (partially guided by assistants), and Self-study (text book and tutorial material for the Matlab environment) 15 h. Course material is in Moodle learning environment. The programming tasks are done in Matlab language on MathWorks Grader online platform.

This course is the part of Computer Science and Engineering open path.

Jeremy Watt, Reza Borhani, Aggelos K. Katsaggelos. Machine Learning Refined (Foundations, Algorithms, and Applications), 2nd edition, Cambridge University Press, 2020.

The course lasts eight weeks. The student follows weekly instructions for laboratory assignments and solves the presented programming problems (five in each week) independently on the The course lasts eight weeks. The student follows weekly instructions for laboratory assignments and solves the presented programming problems (five in each week) independently on the MathWorks Grader online system. The Grader system verifies the completed programming problems and provides basic hints for solving them. The number of correctly solved programming problems is used to grade the course. It is compulsory to pass the first week's assignment and at least one programming problem out of five in the following five weeks. Passing more programming problems increases the course grade. The course utilizes a numerical grading scale 1-5. In the numerical scale zero stands for a fail. Read more about assessment criteria at the University of Oulu webpage.

Tapio Seppänen

1-5/FAIL

Check out the timetable from Peppi: https://opas.peppi.oulu.fi/en/course/521289S/6416