Experimental Data Analysis and Modeling
2024/2025
Recommended prerequisite for participation in the module
The module builds on the project modules in the 1st - 4th semester.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 overall purpose of the project module is for the student to
acquire the ability to analyze and evaluate the application of
methods and techniques within database systems and / or machine
intelligence to solve a specific problem. This involves an
experimental analysis of the properties of the techniques as well
as an experimental evaluation of the results obtained
REASON
Data representation, data analysis, and the ability to draw
intelligent conclusions based on users' wishes and needs are
included as central components in many modern IT systems. Within
this project module, data representation and analysis covers the
use of database management systems to model and store data in
relation to data analysis, transform data into the desired format
and be able to extract information from it using analytical
queries. Intelligent systems are related to machine intelligence,
where the term covers, for example, graphic models, data mining /
machine learning, and autonomous agents. The following references
to database systems and machine intelligence must thus be seen in
this context
In this project module, the project work is primarily driven by empirical evaluations of the techniques / methods used as well as by the general software solution that may be developed through the project work. This may, for example, involve an iterative experimental approach to method development, which may require an essential element of software development, experiment design, and considerations about the statistical significance of the empirical results (such as runtimes, space consumption, and other method-specific properties).
Learning objectives
Knowledge
- use correct concepts (in both writing and speech) notations and symbols.
- demonstrate knowledge and overview of basic techniques in database systems or machine intelligence.
- demonstrate knowledge of relevant methods for model evaluation
Skills
- explain the application of relevant and central techniques within database systems or machine intelligence in relation to a selected problem area
- interpret, communicate and visualize the results of empirical model and data analyzes
Competences
- assess and justify the choice of relevant techniques and methods within database systems or machine intelligence for solving a current problem area
- apply concepts and techniques within database systems or machine intelligence to solve a selected problem
- be able to carry out an empirical evaluation of a relevant model / technique, as well as assess the validity and the statistical significance of the collected empirical results
- apply project management
Type of instruction
Project work
Extent and expected workload
The student is expected to spend 27.5 hours per ECTS, which for this activity means 412.5 hours.
Exam
Exams
| Name of exam | Experimental Data Analysis and Modeling |
| Type of exam | Oral exam based on a project |
| ECTS | 15 |
| Assessment | 7-point grading scale |
| Type of grading | Internal examination |
| Criteria of assessment | The criteria of assessment are stated in the Examination Policies and Procedures |
Additional information
Contact: Study Board for Computer Science via cs-sn@cs.aau.dk or 9940 8854
Facts about the module
| Danish title | Eksperimentel dataanalyse og modellering |
| Module code | DSNDATB520 |
| Module type | Project |
| Duration | 1 semester |
| Semester | Autumn
|
| ECTS | 15 |
| Language of instruction | Danish and English |
| Empty-place Scheme | Yes |
| Location of the lecture | Campus Aalborg |
| Responsible for the module |
Organisation
| Education owner | Bachelor of Science (BSc) in Computer Science |
| Study Board | Study Board of Computer Science |
| Department | Department of Computer Science |
| Faculty | The Technical Faculty of IT and Design |
