CS5939 Data-Driven Systems

Academic year

2024 to 2025 Flexible study

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Available only to students studying the PG Cert/PG Dip/MSc in Data Science (Digital), PG Cert/PG Dip/MLitt Digital Humanities, or PG Cert/PG Dip/MSc Digital Art History

Module coordinator

Dr B Varghese

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

TBC: Module coordinator(s): Computer Science (cs5939.staff@st-andrews.ac.uk)

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

This is an advanced research-focused module that will encourage independent learning. The module has two components. The first is a set of lectures that presents the foundations of distributed systems and techniques that process data. The second is a set of research articles taken from a range of relevant topic areas that will be read and analysed by the student. Data is the fuel of the modern digital economy. It is expected that by 2025 over 180 zettabytes of data will be generated in a year by our smartphone apps, entertainment services and social media sites. How do companies such as Facebook, Google and Netflix manage data at the Internet scale? CS5939 will present the underlying concepts, programming frameworks and large-scale distributed systems essential for storing, analysing and processing data along with application use-cases.

Assessment pattern

Coursework = 100%

Re-assessment

Coursework = 100%

Learning and teaching methods and delivery

Weekly contact

Students should expect to engage in approximately six tutorials over the course of the module, which will be scheduled with an awareness of the pace at which they are progressing, rather than at a fixed time each week. Students should consider the amount of independent study time this module involves when planning their learning.

Scheduled learning hours

13

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

134

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Understand large-scale distributed systems for data-driven computing.
  • Demonstrate knowledge of the use of a programming framework for engineering distributed systems and evaluating them.
  • Be able to analyse research literature on a range of topics on data-driven systems.
  • Understand the challenges involved in developing distributed systems for different application use-cases.