Machine learning with Python
Max amount of FITech students: 500
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.
Course content: Understanding of the basic principles that underlie machine learning. Ability to implement some basic machine learning methods in Python to solve small data science tasks.
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.
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.
Read about Aira’s experiences of Machine learning with Python course here!
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