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Machine learning

Yksittäinen kurssi

Course contents

  • Exploratory data analysis
  • Dimensionality reduction
  • PCA
  • Regression and classification
  • Clustering
  • Deep learning
  • Reinforcement learning
  • Language modeling

Learning outcomes

After completing the course, the students

  • can formalise applications as ML problems and solve them using basic ML methods
  • can perform basic exploratory data analysis
  • understand the meaning of the train-validate-test approach in machine learning
  • can apply standard regression and classification models on a given data set
  • can apply simple clustering and dimensionality reduction techniques on a given data set
  • are familiar with and can explain the basic concepts of reinforcement learning and language modeling.

Teaching methods

The course follows a schedule and includes lectures, self study, assignments, and a project work. The lectures are available online.

Teaching times on campus:

Lectures:

  • Wednesdays at 14:15–16
  • Fridays at 12:15–14

Exercises:

  • Mondays at 8:15–10 (online)
  • Tuesdays at 16:15–18
  • Wednesdays at 8:15–10 (reserved for project support)
  • Thursdays at 14:15–18
  • Fridays at 14:15–16 (online)

Exam:

  • 13.10.–31.10. in the Exam-room on Aalto University campus.
  • Students are required to schedule a time slot (3 hours) during the opening hours of the Exam-rooms (excluding weekends). More information with a detailed schedule will be provided when the course starts.

Workload

Approx. 134 hours of work divided into:

  • Lectures + self-study: 10*(2+2) = 40 hours
  • Assignments: 5 * 9 =45 hours
  • Project work: 30 hours
  • Peer-grading: 8 hours
  • Exam + preparation: 10 hours.

Completion methods

Assignments, project work and an exam on campus.

More information in the Aalto University study guide.

You can get a digital badge after completing this course.

machine learning koneoppiminen ML data analyysi luokittelu regressio klusterointi

Vastuuopettaja

Aalto-yliopisto
Pekka Marttinen, Apulaisprofessori
Aalto-yliopisto
Stephan Sigg, Apulaisprofessori

Lisätietoa kursseista ja niiden suorittamisesta

Aalto-yliopisto
Tiina Porthén

Hakua koskevat kysymykset

FITech-verkostoyliopisto
Fanny Qvickström, Opintoasioiden suunnittelija
Hakuaika alkaa 03.06.2025
Hakuaika alkaa 03.06.2025
Aihe:
Tekoäly ja koneoppiminen
Kurssikoodi:
CS-C3240
Opintopisteet
5 ECTS
Hinta:
0 €
Kurssin taso:
Kurssin ajankohta:
1.9.–19.10.2025
Haun alkamispäivä:
03.06.2025
Viimeinen hakupäivä:
18.8.2025
Vastuuyliopisto:
Aalto-yliopisto
Kuka voi hakea:
Aikuisopiskelija,
Tutkinto-opiskelija
Toteuttamistapa:
Monimuoto-opetus
Paikkakunta:
Espoo
Opetuskieli:
Englanti
Esitietovaatimukset:
Matrix algebra, probability theory, basic programming skills
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