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Module description - Foundation in Data Science
(Grundverständnis Data Science)

ECTS 1.0
Specification Understand basic Data Science concepts and their areas of application.
Level Basic
Content Data has become part of our daily lives and is sometimes referred to as the "oil of the 21st century". Data Science is the discipline that uses scientific and quantitative methods to create value from data. By means of practical applications, central basic concepts are learned in an intuitive and descriptive way, which are encountered again and again in the Data Science course of studies in various forms.
Learning outcomes Students will understand the phases and process of a Data Science & Machine Learning project and will be able to explain the differences as well as advantages & disadvantages of

  • supervised, unsupervised, semi-supervised and reinforcement learning
  • on-line and off-line learning
  • descriptive, predictive and prescriptive modelling

explain in your own words.
Students understand the relationship between cost function, optimization and regularization, overfitting and underfitting, model parameters, and goal metrics, as well as training, validation, and test data using concrete examples.

Students will be able to explain and critically examine Data Science applications in everyday life (e.g., data privacy and discrimination, prediction bias and uncertainty).
Evaluation Mark
Modultype Basic Module
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