Syllabus

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: 10.01.2022 - 08.04.2022

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:

  Substitutes for Courses

Prerequisites

• valid for whole curriculum period:

  Prerequisites

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.

Description