Datan analysointi (4 cr)

Evaluation scale

0-5

Objective

The student understands the significance of data analytics in digitalized operating environment and refining Big data into exploitable form. The student knows the most common methods of data analytics and is able to apply them in practice to existing data.

Content

Data Analytics
- basics
- open data and Mydata
- the common methods
- application of the methods to practice

Materials

Esitetään opintojakson alussa

Completion alternatives

Harjoitustyö 50% Tentti 50%

Student workload

o luennot 15 h o harjoitustyöt 45 h o seminaarit 4 h o itsenäinen työskentely 44 h Yhteensä 108h

Assessment criteria, satisfactory (1)

Sufficient: The student knows the most common techniques used in data analysis tasks. They are able to apply the most common techniques to data analysis and assess their implementation briefly.

Satisfactory 2: The student knows the most common techniques used in data analysis tasks. They are able to choose the techniques for data analysis and apply their technical competence in practice. Additionally, the student is able to assess their implementation superficially.

Assessment criteria, good (3)

Good 3: The student recognizes the benefits of data analytics in utilizing Big data and in the era of digitalization. The student knows the most commonly used techniques in various data analysis tasks. They are able to justify and choose the techniques for data analysis and apply their technical competence to practice. Additionally, the student is able to assess their implementation and justify its development.

Very good 4: The student recognizes the benefits of data analytics in utilizing Big data and in the era of digitalization. The student knows the most commonly used techniques in various data analysis tasks and is able to versatilely justify and choose the correct techniques for data analysis and apply their technical competence to practice. Additionally, the student is able to assess their implementation thoroughly and justify its development.

Assessment criteria, excellent (5)

Excellent 5: The student recognizes the benefits of data analytics in utilizing Big data and in the era of digitalization.The student knows the most commonly used techniques and is able to critically justify the use of the techniques in various data analysis tasks. The student is able to critically justify and select the correct techniques for data analysis regardless of the analyzed data. Additionally, the student is able to assess their technical competence in practice as well as assess their implementation critically and justify its development.

Qualifications

Applies to degree students: the students should have basic skills in Python programming