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Data-alustat (5cr)

Code: TT00CM57-3001

General information


Enrollment
19.08.2024 - 22.09.2024
Registration for the implementation has ended.
Timing
01.08.2024 - 31.12.2024
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
Contact learning
Unit
Teknologia
Teaching languages
Finnish
Degree programmes
Bachelor’s Degree in Information and Communication Technology
Teachers
Ali Hosseini
Jani Sourander
Groups
TTM23SAI
TTM23SAI
Course
TT00CM57

Realization has 10 reservations. Total duration of reservations is 28 h 0 min.

Time Topic Location
Wed 28.08.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 04.09.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 11.09.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 18.09.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 25.09.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 02.10.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 09.10.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 23.10.2024 time 17:00 - 20:00
(3 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 30.10.2024 time 18:00 - 20:00
(2 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Wed 06.11.2024 time 18:00 - 20:00
(2 h 0 min)
Data-alustat TT00CM57-3001
Teams opetus
Changes to reservations may be possible.

Evaluation scale

0 - 5

Content scheduling

Kurssin ensimmäinen puolisko (noin 6 viikkoa) on Alin osuus; hankittu osaaminen todennetaan tentin avulla. Kurssin toinen puolisko (noin 4 viikkoa) on Janin osuus; hankittu osaaminen näytetään 10 minuutin videon avulla, jossa esittelet toteuttamasi, tehtävänannon mukaisen data-alustan.

Objective

The student understands the need for data platforms from the starting points of business success. The student knows how to utilize and develop modern data platforms and automate data processing and data analysis workflows (MLOps, DataOps) in order to make the work steps more efficient and improve the quality of the analysis.

Content

Best practices for data platform development, automation of data processing work steps and data platform architecture planning.

Materials

Linkit oppimateriaaliin, mahdollisiin luentojen tallenteisiin sekä lukuvinkit löytyvät Reppu-alustan "Aloita tästä"-osiosta.

Teaching methods

Teams-luennot, etukäteen nauhoitetut tutoriaalit sekä itsenäisesti tehtävät harjoitukset. Luentojen tallennekäytäntö sovitaan kurssin alussa yhteisesti.

Assessment criteria, satisfactory (1)

The student understands the importance of a data platform for business and can, with assistance, develop a simple data platform.

Assessment criteria, good (3)

The student understands the importance of the data platform, the automation of work steps and knows how to develop a data platform suitable for the company's needs.

Assessment criteria, excellent (5)

The student understands the importance of a data platform for business and knows how to implement a data platform that supports business. The student knows how to automate the work steps of data processing and refine raw data into a versatile data platform.

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