Machine learning with Python

Max amount of FITech students: 1000

Persons without a valid study right to a Finnish university have preference to this course.

This course introduces some of the most widely used machine-learning methods such as regression and clustering methods.

We will discuss these methods in a hands-on fashion using coding assignments. The coding assignments require to solve small machine learning problems using the programming language Python.

The course is organised as six thematic rounds:

1. Components of machine learning,
2. Regression,
3. Classification,
4. Model validation and selection,
5. Clustering and
6. Dimensionality reduction.

After completing this course, you will understand the basic principles that underlie machine learning methods. You will be able to implement some basic machine learning methods in Python to solve small data analysis tasks.

Schedule:

No exam. No particular schedule except for the deadlines for course exercises.

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

You can get a digital badge after completing this course.

More information in Aalto University’s WebOodi course page.

Read about Aira’s experiences of Machine learning with Python course here!

koodaus, koodaaminen, koneoppiminen, regressio, klusterointi, luokittelu