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Data-analytiikka (5op)

Toteutuksen tunnus: R504D137-3001

Toteutuksen perustiedot


Ilmoittautumisaika
02.12.2025 - 31.12.2025
Ilmoittautuminen toteutukselle on käynnissä.
Ajoitus
01.01.2026 - 31.05.2026
Toteutus ei ole vielä alkanut.
Opintopistemäärä
5 op
Lähiosuus
5 op
Toteutustapa
Lähiopetus
Yksikkö
Insinöörikoulutus, tieto- ja viestintätekniikka
Opetuskielet
englanti
Paikat
0 - 30
Koulutus
Machine Learning and Data Engineering
Opettajat
Tuomas Valtanen
Vastuuopettaja
Tuomas Valtanen
Ryhmät
R54D25S
Bachelor of Engineering, Machine Learning and Data Engineering (full time studies), 2025
Opintojakso
R504D137

Arviointiasteikko

H-5

Tavoitteet

You understand the basics of data analytics in data engineering and machine learning.
You can use common data analytics environments and tools for machine learning purposes.
You learn to find insight in data by using explorative data analytics.
You learn methods on how to optimize dataset contents and distributions.
You know how to share your results and exercises via a version control system

Sisältö

Data preparation and pre-processing
Exploratory Data Analysis (EDA): statistical, visual, and other common methods
Finding insight in datasets to optimize their structure
Use of data analytics environments and libraries/modules
Common data analytics tools regarding machine learning

Arviointikriteerit, tyydyttävä (1)

You know the basics of data analytics in data engineering and machine learning.
You are able to apply basic data analytics techniques in data engineering and machine learning tasks.
You can share your results and exercises via a version control system.

Arviointikriteerit, hyvä (3)

You understand the basics of data analytics in data engineering and machine learning.
You are able to apply a variety of data analytics techniques in data engineering and machine learning tasks with a suitable approach, regarding the given dataset at hand.
You can share your results and exercises via a version control system.

Arviointikriteerit, kiitettävä (5)

You understand the basics of data analytics in data engineering and machine learning.
You are able to apply a variety of data analytics techniques in data engineering and machine learning tasks with a suitable approach, regarding the given dataset at hand.
You are able to study and apply advanced tools and approaches regarding exploratory data analytics and dataset optimization with your data
You can share your results and exercises via a version control system.

Esitietovaatimukset

Basics of Python programming, Basics of statistics

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