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MSc Applied Data Science - Renewable Energy

University of Exeter
  • Become immersed in the ‘Big Data revolution’ and develop state-of-the-art data science and AI skills alongside expertise in emerging renewable technologies
  • Based at our stunning Penryn Campus in Cornwall this interdisciplinary programme is run jointly between the departments of Mathematics and Renewable Engineering
  • Designed in collaboration with internationally renowned researchers and industrial partners you will benefit from research-led teaching, practical examples and hands-on activities
  • Develop sought-after, discipline-transcending skills and utilise these through use of modern scientific computing software and a new state-of-the-art Renewable Engineering Facility
  • Gain the skills and experience you need to succeed in the demanding and fast growing data analytics sectors, specifically within renewable technologies.
  • Become immersed in the ‘Big Data revolution’ and develop state-of-the-art data science and AI skills alongside expertise in emerging renewable technologies
  • Based at our stunning Penryn Campus in Cornwall this interdisciplinary programme is run jointly between the departments of Mathematics and Renewable Engineering
  • Designed in collaboration with internationally renowned researchers and industrial partners you will benefit from research-led teaching, practical examples and hands-on activities
  • Develop sought-after, discipline-transcending skills and utilise these through use of modern scientific computing software and a new state-of-the-art Renewable Engineering Facility
  • Gain the skills and experience you need to succeed in the demanding and fast growing data analytics sectors, specifically within renewable technologies.
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Modules

  • Compulsory modules
  • Fundamentals of Data Science
  • Trends in Data Science and AI
  • Data Science and Modelling Dissertation
  • Tackling Sustainability Challenges using Data and Models
  • Renewable Energy Systems
  • Options modules
  • Advanced Marine Renewable Energy
  • Advanced Wind Energy
  • Solar Energy Research and Innovation
  • Requirements

    Listed below are the documents required to apply for this course.
    1 year

    Duration

    Sep 2024

    Start Month

    Aug 2024

    Application Deadline

    Upcoming Intakes

    • September 2024

    Mode of Study

    • Full Time