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  • DeadlineStudy Details: MSc 1 year full-timeUK home students , 2 years part-time UK home students

Masters Degree Description

The MSc Data Science programme is designed as a conversion master’s to introduce graduates from diverse backgrounds to the field of data science. The programme aims to provide a comprehensive foundation in data analysis, statistical methods, probability models, big data, machine learning and modern data imputation and processing technologies. Students will learn to extract insights from complex data sets, use machine learning algorithms, and apply predictive analytics in various sectors.

The course provides broad knowledge and practical skills needed to develop software systems to generate predictive, descriptive, diagnostic, preventive and prescriptive analytics from huge and complex real-world datasets. The practical skills include programming, analyses of algorithms, statistical & probabilistic techniques, neural networks, large language models, distributed processing and data science. The integral academic writing, research and project management skills and a mandatory independent dissertation/project in the final semester further underpin application of the industry-style professional approaches as well as an appreciation of future directions of technological advances and research.

Entry Requirements

  • A relevant honours degree 2:2 or above
  • IELTS (Academic) overall 6.5 with no individual component less than 6.0

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Fees

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Student Destinations

Computer science offers an incredibly wide range of high demand careers at the forefront of software-based technologies, such as:

  • Data scientists
  • Artificial Intelligence engineers
  • Natural language processing engineers
  • Information systems developers
  • Distributed data processing administrators
  • Healthcare informatics experts
  • IT consultants/project managers
  • Systems architects
  • Distributed applications developers
  • Big Data analysts, and;
  • Financial technology experts etc.

Module Details

Semester 1

  • Advanced Analyses of Algorithms
  • Statistical & Mathematics Methods for AI & DS
  • Big Data Analytics

Semester 2

  • Distributed Data Processing
  • Natural Language Processing
  • Research Methods & Project Management

Semester 3

  • Dissertation

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