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MSc Intelligent Vision

University of Lincoln

This programme combines a computing core with computer vision, data science, and machine learning specialisms. This offers students the theoretical and practical experience needed to develop the innovative solutions required in a dynamic and innovative technology sector.

Course content is informed by the work and research carried out in the School, especially in machine learning and Computer Vision, as well as related areas. This approach aims to ensure content is both leading-edge and underpinned by the latest thinking in the field.

The programme enables students to explore topics including advanced artificial intelligence, computer vision, machine learning, applied signal and image processing, and neural computing.

Students also have the opportunity to undertake a substantial research project focusing on an area of personal and professional interest, through the development of a dissertation and substantive software implementation. This programme aims to provide students with skills spanning two key disciplines of modern computing and its applications, namely imaging and data science, and their combined use. Such skills are in high demand not only in academia and industries dealing with imaging technologies and related challenges, but also in many other areas where analytical and multidisciplinary mindsets and skills are critical. Some students may choose to continue towards doctoral level, including within the School of Computer Science.

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Modules

  • Advanced Artificial Intelligence
  • Advanced Machine Learning
  • Applied Signal and Image Processing
  • Big Data Analytics and Modelling
  • Computer Vision
  • Frontiers of Machine Learning and Computer Vision Research
  • Neural Computing
  • Research Methods (MSc Computer Science)
  • Research Project
  • Requirements

    Listed below are the documents required to apply for this course.
    £17,600 Per Year

    International student tuition fee

    1 year

    Duration

    Oct 2024

    Start Month

    Sep 2024

    Application Deadline

    Upcoming Intakes

    • October 2024

    Mode of Study

    • Full Time