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Offshore and Ocean Technology with Offshore Renewable Energy (PgCert PgDip) logo
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Offshore and Ocean Technology with Offshore Renewable Energy (PgCert PgDip)

Cranfield University
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Degree MSc
Duration 12 months
Delivery On-campus
Location Cranfield, United Kingdom
Language English

Program Overview

The Offshore and Ocean Technology with Offshore Renewable Energy (PgCert PgDip) at Cranfield University is a MSc programme in Humanities over 12 months, delivered On-campus. This programme equips graduates with advanced knowledge and practical skills for professional and academic careers in the field.

Students gain a rigorous grounding in both the theoretical foundations and applied dimensions of humanities. The programme combines coursework, research components, and practical projects that develop critical thinking, problem-solving, and specialist expertise relevant to industry and research needs.

Graduates of the Offshore and Ocean Technology with Offshore Renewable Energy (PgCert PgDip) programme are well-prepared for careers in academia, industry, government, and the private sector across United Kingdom and internationally. The programme provides an internationally recognised qualification within the Bologna higher education framework.

Key Program Features

  1. Duration: 12 months
  2. Language of instruction: English
  3. Study mode: On-campus
  4. English requirement: IELTS 6.5
  5. Location: Bedford, United Kingdom

Career Opportunities

Graduates of the Offshore and Ocean Technology with Offshore Renewable Energy (PgCert PgDip) programme are prepared for diverse careers in humanities:

  1. Researcher / Academic
  2. Cultural Programme Manager
  3. Editor / Writer
  4. Translator / Interpreter
  5. Museum Curator
  6. Communications Specialist

Program Curriculum

Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the compulsory and elective (where applicable) modules which are currently affiliated with this course. All modules are indicative only, and may be subject to change for your year of entry.


Course modules

Engineering route compulsory modules

Artificial Intelligence for Sustainability

Aim
    The sustainability industry has been experiencing growing challenges driven by decarbonisation, examples include the increasing difficulties in balancing energy systems caused by the penetration of uncertain and less controllable renewable generation. Nevertheless, the widespread installation of measurement and control units have enabled innovations in data analytics, especially is using AI to support planning and operation in sustainability industry, which effectively addresses the challenges. The scientific and technical concepts of machine learning and AI methods/tools and their potential advantages in the sustainability sector will be taught in this module. The module aims to provide the students with data analytical skills from machine learning and AI technology, and evaluate the advantages/disadvantages of their applications in the sustainability industry. Additionally, the module aims to provide students with essential skills (e.g. computer programming and coding in Python) for applying machine learning in resolving practical problems.
Syllabus
    • Fundamentals of AI and Machine Learning
    • Neural Networks
    • Convolutional Neural Networks
    • Strategies of Training of neural networks
    • Classification and Regression Trees
    • Unsupervised Learning
    • Practical case studies
Intended learning outcomes

On successful completion of this module you should be able to:

  1. Critically analyse the state-of-the-art of the applications of machine learning (ML) and AI technology in the sustainability sector;
  2. Identify and assess the requirements of different AI/ML techniques and their contributions to improve the planning and operation in the sustainability sector;
  3. Implement AI/ML methods, and assess their performance through a realistic case study
  4. Evaluate the advantages and disadvantages of particular AI techniques within the context of the sustainability sector 

    Admission Requirements

    Academic Requirements

    A first or second class UK Honours degree (or equivalent) in a related science or engineering discipline. Other recognised professional qualifications or several years relevant industrial experience may be accepted as equivalent; subject to approval by the Course Director.

    Applicants who do not fulfil the standard entry requirements can apply for the Pre-Masters programme, successful completion of which will qualify them for entry to this course for a second year of study.

    Students requiring a Tier 4 (General) visa must ensure they can meet the English language requirements set out by UK Visas and Immigration (UKVI) and we recommend booking aIELTS for UKVI test.

    English Proficiency: IELTS 6.5 or equivalent.

    Tuition & Financial Information

    Detailed tuition information is not available. Please contact the university for the most current tuition and fee information.

    Application Deadline

    Please contact the university for application deadline information.

    About Cranfield University

    Cranfield University logo

    Cranfield University

    Cranfield, United Kingdom

    Cranfield University is a distinguished institution of higher education committed to academic excellence, innovative research, and preparing students for leadership in their chosen fields. The...

    University Profile
    Application Information
    • Start Date 2017-10-01
    • Language English
    • Duration 12 months
    Apply Now
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