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MSc Data Science and Computational Intelligence with Placement Year

Coventry University

Course overview

Study level: Postgraduate

This master’s course aims to respond to the demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies.

  • The main theme throughout this course is automatic big data processing and information retrieval through machine learning, neural network and evolutionary computing.
  • We aim to cover how to apply cutting-edge machine learning techniques to analyse big datasets, assess the statistical significance of data mining results and perform advanced data mining tasks.
  • We will introduce you to important frameworks which may include Hadoop Map Reduce, Spark, applications of relational databases and NoSQL databases in combination with easy to use and powerful development tools such as Python, R and Matlab.
  • We will look at emerging theories, practices, approaches and management of distributed and intelligent computing systems, examining a wide range of case studies to see how applications have been developed and for what purposes, such as steganography detection system for colour stego images.
  • The focus of the course is on applications of data science methods and tools, combined with computational intelligence techniques for data-driven problem solving including the analysis, interpretation and visualisation of complex data, which is in increasing demand in fields such as marketing, pharmaceutics, finance, transportation, medicine, and management.
  • You will have the option to apply for a ‘work placement’ opportunity2, designed to further develop your skills and knowledge with the aim of maximising your employability prospects. See modules for more information.
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Requirements

Listed below are the documents required to apply for this course.
2 years

Duration

May 2024

Start Month

Apr 2024

Application Deadline

Upcoming Intakes

  • September 2024
  • May 2024
  • September 2025

Mode of Study

  • Full Time