ADSE3200 Visualization Course description

The students will gain knowledge of and insight into how to use data visualisation to present information, for example statistics, in a more understandable way. The students will learn to use different methods of processing data, so that they are easier to work with.

No requirements over and above the admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:

Knowledge

The student:

• is familiar with terminology and concepts used in the field of visualisation
• is familiar with the history of the field
• is familiar with fundamental perception theory
• is capable of explaining different types of information and what kind of visualisation techniques are expedient
• is capable of explaining how visualisation can make it easier to understand large amounts of data
• is capable of explaining typical limitations in the visualisation of complex data sets
• is capable of explaining what methods can be used to visualise different types of data

Skills

The student is capable of:

• identifying the properties of a data set and deciding what visualisation method is most expedient
• evaluating whether visualisation will make it easier to understand a data set, and what method(s) will give the best result
• using specific tools to create visualisations
• using visualisation as a tool

General competence

The student is capable of:

• using visualisation as a tool for understanding and communicating complex contexts

Teaching comprises a combination of lectures, workshops and practical exercises. The students work independently in groups (maximum 3 people) and individually on specific issues in the field of visualisation.

None.

Portfolio assessment subject to the following requirements:

• group work (maximum 3 people, written submission of 3,000-5,000 words)
• individual work (written submission of 3,000-5,000 words)

One overall grade is awarded for the portfolio. Both parts of the portfolio must be awarded a grade E or better for a student to successfully pass the course.

The exam result can be appealed.

In the event of resit and rescheduled exams, another exam form may also be used or a new assignment given with a new deadline. If oral exams are used, the result cannot be appealed.

All.

The students shall acquire knowledge of database design and skills in the use of relational databases. Furthermore, they shall develop skills in the construction and maintenance of databases and insight into multi-user and multi-layer database architecture. They will gain knowledge of XML and insight into programming for databases.

No requirements over and above the admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student is capable of:

• explaining what a database system is and what it consists of
• explaining what XML is and how it is used
• explaining what transactions are and how they are carried out
• explaining the use of indices and different ways of storing the files physically
• explaining what a data warehouse is and how it differs from a database system
• explaining how the combination of ER modelling and normal forms provides well-structured relational databases

Skills

The student is capable of:

• designing databases with the help of ER modelling
• creating databases and using them with the help of the SQL language
• drawing ER models and generating database scripts with the help of software

General competence

The student is capable of:

• explaining the documentation and design of databases with ER models