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Data analytics project (5op)

Toteutuksen tunnus: T42D39OJ-3001

Toteutuksen perustiedot


Ilmoittautumisaika
16.03.2020 - 02.11.2020
Ilmoittautuminen toteutukselle on päättynyt.
Ajoitus
09.11.2020 - 11.12.2020
Toteutus on päättynyt.
Opintopistemäärä
5 op
Lähiosuus
0 op
Virtuaaliosuus
5 op
Toteutustapa
Etäopetus
Yksikkö
Tradenomikoulutus, tietojenkäsittely
Toimipiste
Minerva, Kauppakatu 58, Tornio
Opetuskielet
suomi
Koulutus
Business Information Technology
Opettajat
Pekka Reijonen
Vastuuopettaja
Pekka Reijonen
Ryhmät
T42D19S
Business Information Technology (day time learning) Tornio autumn 2019
Opintojakso
T42D39OJ

Arviointiasteikko

H-5

Sisällön jaksotus

On campus: 09.11.2020 - 11.12.2020

Tavoitteet

In this module, you carry out a data analytics project based on a real task from the working life. The project is following the objectives and the requirements defined by the customer. During the project, you analyse the requirements, select the tools and methods of data analysis and visualization, and implement the project task. The module is implemented through a problem-based learning approach. Teachers coach the learning process, lecture, guide the practical work, organize workshops, and provide consultancy to the students. The prerequisite for this course is the possession of the relevant subject matter knowledge and skills in Statistics, Data Analytics, and relevant tools for data representation and visualization.

Sisältö

Tieto puuttuu

Aika ja paikka

On campus: 09.11.2020 - 11.12.2020

Opetusmenetelmät

Problem-based and team based learning may be applied where applicable. Students will seek information and solve problems related to subject guided. Different activating vocational teaching methods will be used depending on the group taught and the facilities available. If applicable, conventions from selected areas in software industry may be used as a part of teaching. Teacher guides the learning process by short introductory lectures and/or initial subject related material to be studied before practical work. Teacher prepares the setting for learning and provides coaching for the students. Teaching sessions may take place on campus and online. The main focus will be on guided knowledge searching and practical work on it.

Harjoittelu- ja työelämäyhteistyö

Software industry conventions are used. This course may include a case company selected by the university. In addition, students are able to propose your own case companies, whose business information and data analytics they would like to develop. Students must provide a free form commission agreement from their own case companies.

Toteutuksen valinnaiset suoritustavat

Before the course starts, students may propose to the course teachers their personal implementation plan. The plan must be realistic and result in verificable development in the targeted competence(s). In addition, guidance from MIGRI and student visa must be taken into account. Course teachers accept or reject student's plan based on their own consideration.

Opiskelijan ajankäyttö ja kuormitus

The student's estimated workload of this implementation is 135 h as follows:
Roughly half of which is Independent individual and teamwork guided when needed.
Rest of hours will be mostly learning the subject with guided practical and knowledge seeking exercises.

Arviointikriteerit, tyydyttävä (1)

Evaluation target: You can specify, plan and implement a Data Analytics project according to the given requirements.

Satisfactory
You understand the main activities in a Data Analytics project and can implement simple project tasks with supervision and guidance.

Arviointikriteerit, hyvä (3)

Good
You specify the project activities according to the given requirements and can choose appropriate tools and methods of data analysis.

Arviointikriteerit, kiitettävä (5)

Excellent
You understand comprehensively the Data Analytics project activities and can implement them independently. You can also evaluate different alternatives and can choose an effective implementation according to the project objectives and requirements.

Esitietovaatimukset

NULL

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