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.
Increasingly large amounts of data are being collected that
relate to societal and industrial processes. This data spans a
variety of structures and includes tabular data and more complex,
Successful value creation from such data involves data integration, preparation, and management, in addition to data analysis and machine learning that supports data exploration and knowledge extraction. These are typically data and computationally intensive processes that call for advanced data processing, data analysis and machine learning.
Knowledge about data preparation and processing techniques relevant for the project domain.
Knowledge about relevant data analysis and machine learning methods for solving data science problems involving data ranging from tabular data to complex, graph-structured data.
Identify a concrete and relevant application domain for which one or more suitable data sources are available.
Develop a data science solution for an application domain.
Perform data preparation and apply data analysis and machine learning methods and analyze the results.
Document the developed solution and the results, including the knowledge gained about the domain.
Reason about relevant techniques and methodologies for integrating and processing available data.
Reason about relevant data analysis and machine learning methods.
Reflect on the applied methods and techniques as well as the results obtained.
|Name of exam
|Data and Computationally Intensive Systems
|Type of exam
Oral exam based on a project
|7-point grading scale
|Type of grading
|Criteria of assessment
|The criteria of assessment are stated in the Examination Policies and Procedures
|Data-og beregningsintensive systemer
|Language of instruction
|Danish and English
|Location of the lecture
|Responsible for the module
|Study Board of Computer Science
|Department of Computer Science
|The Technical Faculty of IT and Design