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Foundations of Data Science I

Short name: FDS1
SITS code: BUCI069H4
Credits: 15
Level: 4
Module leader: Felix Reidl
Lecturer(s): Felix Reidl
Online material:

Module outline

This module covers fundamental aspects of data science and analytics. Students develop the basic mathematical knowledge and skills needed for further studies in the BSc Data Science programme, and needed by data scientists/analysts in general. These include basic elements of linear algebra, preliminaries for calculus, as well as discrete probability theory and fundamentals of statistics. The module will show you how to use the popular and powerful language Python to solve computational tasks from these mathematical subjects. In particular, this module will get you acquainted with popular Python libraries and packages for programming to solve problems arising from linear algebra, probability theory and statistics.


On successful completion of this module, you will:

  • Demonstrate satisfactory knowledge of basic linear algebra and matrix theory.
  • Demonstrate satisfactory knowledge of basic discrete probability theory and statistics.
  • Demonstrate satisfactory knowledge of relevant Python libraries and packages.
  • Demonstrate satisfactory skills of programming in Python to solve computational tasks from linear algebra and discrete probability theory.
  • Understand the link between the basic knowledge acquired from the module and data science/analytics applications.


Indicative timetables can be found in the handbooks available on programme pages. Personalised teaching timetables for students are available via My Birkbeck.


Coursework (20%) One two hour written examination (80%).