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Data Science 7,5 Credits

Course Contents

The exponential growth of the digital universe, particularly in the form of storage and computing power in recent decades, enables companies to accumulate huge amounts of data at moderate cost. Accompanying this technological shift is a widespread realization that collected data contain potentially valuable information. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, through data analysis.

The course includes the following elements:
- Fundamental tasks in data analysis, i.e., classification, regression, clustering and association rules
- Basic machine learning techniques for classification, regression, clustering and association rules
- Organization of a data analysis project, i.e., preprocessing, modeling and evaluation
- Tools and techniques for large scale data analysis
- Software tools for data analytics
- Data analytics applied in different engineering and business domains

Prerequisites

The applicant must hold the minimum of a bachelor’s degree (i.e the equivalent of 180 ECTS credits at an accredited university) with at least 90 credits in computer engineering, electrical engineering (with relevant courses in computer engineering), or equivalent. The bachelor’s degree should comprise a minimum of 15 credits in mathematics. Proof of English proficiency is required.

Level of Education: Master
Course code/Ladok code: TDSR29
The course is conducted at: School of EngineeringLast modified 2019-12-16 07:40:55

Content updated 2020-08-25