Modules

Core Modules (30 credits)

  • CS6405 Data Mining (5 credits) – Dr Alejandro Arbelaez, Semester 2
  • CS6421 Deep Learning (5 credits) – Prof Gregory Provan, Semester 2
  • ST6030 Foundations of Statistical Data Analytics (10 credits) - Dr Michael Cronin & Dr Supratik Roy, Semester 1
  • ST6033 Generalised Linear Modelling Techniques (5 credits) - Dr Michael Cronin, Semester 2

Database Modules

Students who have adequate database experience take:

  • CS6408 Database Technology (5 credits) - Dr Colin McCormack, Semester 1

Students who have not studied databases take:

  • CS6503 Introduction to Relational Databases (5 credits) - Dr Kieran Herley, Semester 1

Elective Modules (30 credits) - All selections are subject to the approval of the programme coordinator

Students must take at least 10 credits of CS (Computer Science) modules and at least 10 credits of ST (Statistics) modules from those listed below:

  • CS6322 Optimisation (5 credits) - Dr Steve Prestwich, Semester 1
  • CS6409 Information Storage and Retrieval (5 credits) - Dr Alejandro Arbelaez, Semester 2
  • CS6420 Topics in Artificial Intelligence (5 credits) – Prof Barry O’Sullivan, Semester 1
  • ST6034 Multivariate Methods for Data Analysis (10 credits) - Dr Amir Jalali, Semester 2
  • ST6035 Operations Research (5 credits) – TBC, Semester 1
  • ST6036 Stochastic Decision Science (5 credits) – TBC, Semester 2
  • ST6040 Machine Learning and Statistical Analytics I (5 credits) - Dr Eric Wolsztynski, Semester 1
  • ST6041 Machine Learning and Statistical Analytics II(5 credits) - Dr Eric Wolsztynski, Semester 2

Programming Modules

Students who have adequate programming experience take:

  • CS6422 Complex Systems Development (5 credits) – Prof. Gregory Provan, Semester 1
  • CS6423 Scalable Computing for Data Analytics (5 credits) - Prof. Gregory Provan, Semester 2

Students who have not studied programming take:

  • CS6506 Programming in Python (5 credits) - Dr Kieran Herley, Semester 1
  • CS6507 Programming in Python with Data Science Applications (5 credits) - Dr Kieran Herley, Semester 2


PART 2 (30 credits)

A student who obtains an aggregate mark of at least 60% across the taught modules, and not less than 40% in the Dissertation in Data Science and Analytics will be eligible for the award of the MSc Data Science and Analytics.

Eligible students select one of the following modules:

  • CS6500 Dissertation in Data Analytics (30 credits) - Semester 3
  • ST6090 Dissertation in Data Analytics (30 credits) - Semester 3

School of Computer Science and Information Technology

Scoil na Ríomheolaíochta agus na Teicneolaíochta Faisnéise

School of Computer Science and Information Technology, Western Gateway Building, University College Cork, Western Road, Cork, Ireland

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