Kursen ingår i dessa läroplaner och studiehelheter

Kursens undervisningsperiod

  • 3 (2024-01-01 till 2024-03-17)
  • 4 (2024-03-18 till 2024-07-31)

Nivå/kategori

Yrkesstudier

Undervisningsspråk

Engelska

Kurstyp

Obligatorisk

Cykel/nivå

Högre yrkeshögskoleexamen

Rekommenderat studieår

1

Omfattning

5 sp

Kompetensmål

The aim of the course is to provide the student with
the necessary tools for handling big data sources
for machine learning modeling.

Läranderesultat

Knowledge
At the end of the course, the student is expected
to understand when it is needed to use
supercomputer facilities for solving analytical
problems.
Skill
The student will be able to run machine
learning algorithms in supercomputer facilities.
Moreover, the student will be able to run machine
learning models using spark and dask frameworks.

Innehåll

The students get an overview of machine
learning and how to utilize big data.
The areas of descriptive and predictive modelling
are introduced for small data, and the students
are then given an explanation for how similar
models can be modified to work with big data.
The students are introduced to the analytical
process; data-related requirement handling,
domain knowledge, modelling and verification of
results.

Förkunskaper

Basic python programming skills are required.
Previous courses in Machine Learning for Predictive
and Descriptive problems are recommended.

Litteratur

Hamstra, M., & Zaharia, M. (2013). Learning Spark:
lightning-fast big data analytics. O'Reilly &
Associates.

Daniel, J. (2019). Data Science with Python and
Dask. Simon and Schuster.

https://docs.csc.fi/support/tutorials/ml-guide/

Studieaktiviteter

  • Föreläsningar - 30 timmar
  • Basgruppsarbete - 70 timmar
  • Självstudier - 35 timmar

Arbetsbelastning

  • Kursens totala antal arbetstimmar: 135 timmar
  • Varav självstyrda studieformer: 135 timmar
  • Varav schemalagda studier: 0 timmar

Undervisningsform

Flerformsundervisning (delvis nätundervisning handledd eller självstudier)

Examinationskrav

To pass this course, the student should present a
final project in group or individually where they
use big data facilities for machine learning
modeling.

Lärare

  • Björk Kaj-Mikael
  • Espinosa Leal Leonardo
  • Scherbakov-Parland Andrej

Examinator

Espinosa Leal Leonardo

Kursens hemsida

Antal kursplatser

Ingen begränsning (31 studenter anmälda)

Delprestation i kraft till

12 månader efter kursens slutdatum

Kursanmälningstid

2023-11-24 till 2023-12-22

Kurs och studieplanssökning