LEARNING OUTCOMES
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.
Credits: 2
Schedule: 04.04.2022 - 04.07.2022
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Alex Jung, Shamsiiat Abdurakhmanova
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
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 organized 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.
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
This hands-on course is an excellent follow-up course to the more theoretic course CS-C3240 Machine Learning.
Teaching Period:
Course Homepage: https://mycourses.aalto.fi/course/search.php?search=CS-EJ3211
Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.