Data Analytics and Data Visualisation (5cr)

Objectives (course unit)

The objective of the course is to develop the skills to process, analyse and visualise data. The course provides the skills to utilise data in decision-making in the health care sector.

After completing the course, the student
- know the key data analytics terms and concepts
- know the principles of data collection, storage and analysis methods in the context of healthcare
- knows how to use data analytics as a decision-making tool
- know the most common data management and visualization methods
- understand the meaning and uses of data in healthcare processes

Content (course unit)

Key concepts: definition of healthcare data, Big Data, data visualisation, data preprocessing, data storage and its technologies, API interfaces
Data and its categories
Data processing and utilization methods
An overview of data storage technologies and APIs to utilize them
Data visualization and visual data analytics
Data analytics as part of healthcare decision-making

Assessment criteria, satisfactory (1-2) (course unit)

The student
- knows how to process data
- can do data analyzes and visualizations based on examples
- knows some concepts related to data and analytics as well as some uses of data in the area of ​​healthcare

Assessment criteria, good (3-4) (course unit)

The student
- knows how to process data as needed
- can analyze and make data visualizations and understand their meaning in the processing context
- knows the most important concepts related to data and analytics, as well as several uses of data in the area of ​​healthcare
- understand the importance of data in healthcare management processes

Assessment criteria, excellent (5) (course unit)

The student
- knows how to handle data versatilely in a way that suits the context
- can analyze and make versatile data visualizations and understand their meaning in the processing context
- knows the most important concepts related to data and analytics, as well as several uses of data in the area of ​​healthcare
- understand the importance of data in healthcare management processes

Location and time

Etäopetus parittomina viikkoina alustavasti:

Perjantai 15.8 klo 8:30 - 11:45
Perjantai 29.8 klo 8:30 - 11:45
Perjantai 12.9 klo 8:30 - 11:45
Perjantai 26.9 klo 8:30 - 11:45
Perjantai 24.10 klo 8:30 - 11:45
Perjantai 21.11 klo 8:30 - 11:45

Exam schedules

Ei tenttiä.

Assessment methods and criteria

Kurssin arvosana määräytyy harjoituksista ja harjoitustyöstä kerättävien suorituspisteiden perusteella. Läpäisyyn ja arvosanaan 1 vaaditaan vähintään 30% pisteistä, maksimiarvosanaan vähintään 90% pisteistä (muut arvosanat lineaarisesti tältä väliltä).

Assessment scale

0-5

Teaching methods

Kontakti-opetus, etäopetusta teamsissa, oppimistehtävinä opetusviikkojen teemoihin littyviä harjoituksia sekä harjoitustyö.

Learning materials

Materiaali moodlessa, sisältäen linkkejä aihepiirin englanninkieliseen aineistoon (mm. työkalujen ohjeet ja dokumentaatio)