Programme Outlines and Overviews

Data Science 7.5 credits

Course content

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:

Organization of a data analysis project and its different phases, i.e., business understanding, data understanding, preprocessing, modelling, evaluation and deployment
Understanding and preparing data for analysis
Fundamental tasks in data analysis, i.e., classification, regression, clustering, association analysis and deviation analysis
Software tools for data analytics
Basic machine learning techniques for finding patterns, explanations and predictions
Data analytics applied in different engineering and business domains

Entry requirements

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, Computer Science or Electrical Engineering (with relevant courses in computer engineering), or equivalent, or passed courses at least 150 credits from the programme Computer Science and Engineering. The bachelor’s degree should comprise a minimum of 15 credits in mathematics. Proof of English proficiency is required.

Level: Second cycle

Course/Ladok-code: TDSR22

School: School of Engineering