Welcome to ST207 Databases!

Course description

This course runs in the Autumn Term (AT), with lectures on Tuesdays and seminar sessions on Thursdays and Fridays

The course covers concepts related to relational and other types of database management systems, including multimedia, spatiotemporal and NoSQL databases. The topics covered will include relational database design; Structured Query Language (SQL) for basic database manipulation; complex SQL queries using aggregate operators and subqueries; integrity constraints, triggers, views and indexing structures; transaction management and concurrency; NoSQL databases such as key-value stores, document, and graph databases; multimedia and spatiotemporal databases.

The course will demonstrate how various theoretical principles are implemented in practice in a database management system, such as MySQL or SQLite, and also in NoSQL, multimedia and spatiotemporal database software.

Lectures are two hours long, covering the main concepts related to the topic being discussed and some hands-on exercises to demonstrate such concepts. Seminars are structured to use different tools for database design and programming. During some seminars, those who opt-in will use some generative AI tools to explore new learning strategies. These learning activities will be designed as part of the GENIAL project and will help us understand the potential of generative AI in higher education.


Formative assessment is carried out on a weekly basis, during seminar and self/group study activities.

Summative assessment will work as follows:

  • Two continuous assessments (each worth 20% of the final mark), respectively assigned in week 4 and week 9. You will have approximately two weeks to submit your solution.
  • Group project, worth 60% of the mark, discussed and approved with the lecturer by the end of term and carried out in the 4 following weeks. In this, the group will have the opportunity to demonstrate their ability to develop a database for a particular application.

Indicative reading

Teaching staff

Dr. Marcos Barreto 
e:  m.e.barreto@lse.ac.uk
w:  marcosebarreto.github.io

Dr. Anica Kostic 
e:  a.kostic@lse.ac.uk
w:  https://www.lse.ac.uk/statistics/people/anica-kostic