Content, progress and pedagogy of the module

Disclaimer. This is an English translation of the module. In case of discrepancy between the translation and the Danish version, the Danish version of the module is valid.

PURPOSE
The purpose of the project module is for students to gain knowledge, skills, and competences in relation to the selection and use of advanced data mining techniques in relation to specific application scenarios for the purpose of extracting insights from large scale, heterogenous, complex, and unstructured data

REASONS
Data mining refers to the process of analyzing large data sets (big data) to extract or discover patterns useful in the contexts of a particular application scenarios. Data mining can make use of statistical learning and statistical methods in general. Applications of data mining span domains such as retail, entertainment, media, Web, manufacturing, and IoT. For example, purchase data collected in retail can be mined to understand customer purchasing patterns that may be utilized for advertising

Learning objectives

Knowledge

• demonstrate knowledge of the functioning and pertinent properties of main data mining techniques, including techniques that target unstructured data and semi-structured data 

• demonstrate knowledge of the applicability of data mining techniques in relation to different types of data and use cases 

• Demonstrate knowledge of the big data technologies and their impact on scalability 

• Demonstrate knowledge of the methods and techniques required to measure and validate the quality and reliability of the results produced by the various data mining techniques

Skills

• find and pre-process datasets in order to employ data mining techniques to solve a specific data analysis problem 

• choose and apply appropriate data mining techniques to extract relevant insight from datasets within a given application scenario 

• combine different data mining techniques in novel ways to solve a realistic application scenario 

• carry out a systematic evaluation of data mining techniques 

• understand and utilize Big Data technologies and methods to apply data mining approaches to large datasets 

Competences

• identify possible alternative solutions employing relevant data mining techniques to a given application scenario and argument their possible advantages and disadvantages 

• reflect on the solutions and methods used

Type of instruction

Project work

Extent and expected workload

It is expected that the student uses 30 hours per ECTS, which for this activity means 450 hours

Exam

Exams

Additional information

Contact: The Study board for Computer Science at cs-sn@cs.aau.dk or 9940 8854