Welcome to ST207 - Databases!

Your learning pathway through relational, NoSQL, multimedia, spatiotemporal, and vector databases!

In this course, we cover:

  • relational database modelling & structured query language (SQL)
  • database administration (integrity constraints, triggers, views, concurrency control, and fault recovery)
  • NoSQL databases: key-value stores, objects, and graph databases
  • Multimedia and spatiotemporal databases
  • Vector databases and large language models (LLMs)
Lecture and seminar delivery

This course runs in the Autumn Term (AT), with lectures and seminar sessions scheduled as follows:

Timetable for lecture and seminar sessions for the ST207 - Databases course.

Assessment

  • Formative assessment: weekly activities during seminars and self/group study.
  • Summative assessment:
    • Two individual assignments (each worth 20% of the final mark, in Weeks 4 and 9).
    • Group project (worth 60% of the mark, in Week 11)

Indicative reading

  • R. Elmasri and S. B. Navathe. Fundamentals of Database Systems, 7th edition (Global Edition). Pearson, 2016.
  • G. Powell. Database Modeling Step-by-Step, CRC Press. Taylor & Francis, 2019.
  • A. Beaulieu. Learning SQL: generate, manipulate, and retrieve data, 3rd edition. O'Reilly, 2020.
  • E. Foster and S. Godbole. Database Systems: a pragmatic approach, 3rd edition. CRC Press, 2023.
  • E. Sciore. Database Design and Implementation. 2nd edition. Springer, 2020.
  • S. Bradshaw, E. Brazil, K. Chodorow. MongoDB: the definitive guide, 3rd edition. O’Reilly, 2019.
  • I. Robinson and J. Webber and E. Eifrem. Graph Databases. 2nd edition. O’Reilly, 2015.

Teaching staff

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

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


Pre-sessional course
Consider taking the Pre-sessional course on Python for Statistics