The analysis of larger datasets is a productive way to obtain new empirical insights into real-world phenomena. With a critical attitude to the creation and interpretation of data, this course provides a basic step-by-step hands-on introduction of the processes of data gathering, data cleaning, explorative data analysis and visualization. As an example of an object-oriented language useful for this purpose, we use Python with its large array of functional modules (libraries) and integrations for our exercises. The process of selection, cleaning and analysis of data lead us to discuss reliability, predictability, categorization and information security. This module is anchored in the Research group of Communication, Media and Information technologies, Department of Electronic Systems.
Course module. Please refer to §17 of the curriculum about the structure and content of the programme.
|Name of exam
|Introduction to Scripting, Data Mining and Machine Learning
|Type of exam
Written or oral examDetermined in the semester description.
|7-point grading scale
|Type of grading
|Criteria of assessment
|The criteria of assessment are stated in the Examination Policies and Procedures
|Introduktion til scripting, dataminering og maskinlæring
|Language of instruction
|Location of the lecture
|Campus Copenhagen, Campus Aalborg
|Responsible for the module
|Study Board of Techno-Anthropology and Sustainable Design
|Department of Sustainability and Planning
|The Technical Faculty of IT and Design