Overview
This MSc programme at Imperial College London focuses on the intersection of environmental engineering and data science, preparing students to address pressing global environmental issues. The curriculum is designed to enhance technical expertise in environmental practices while incorporating computational methods and statistical modelling techniques. The course structure is tailored to provide a comprehensive understanding of sustainability concepts and engineered solutions aimed at conserving resources and protecting both the environment and human health.
Why Environmental Engineering with Data Science at Imperial?Imperial College London is renowned for its academic excellence and innovative research. The university consistently ranks among the top institutions globally, particularly in engineering and technology disciplines. With strong industry partnerships, students benefit from access to cutting-edge facilities and resources. The programme's unique focus on data science complements traditional environmental engineering, making graduates highly attractive to employers in various sectors.
Tuition Fee BreakdownThe tuition fees for the MSc in Environmental Engineering with Data Science are structured as follows:
- Home Students: £18,500 per year
- International Students: £42,900 per year
Visit the Fees and Funding section for a breakdown in your local currency.
SyllabusThe programme includes a range of core modules designed to provide a solid foundation in both environmental engineering and data science:
- Environmental Fluid Mechanics
- Statistical Modelling
- Urban Hydrology and Urban Drainage
- Machine Learning
- Chemistry and Microbiology for Environmental Engineering
- Contaminated Land and Groundwater
- Design Project: Data Science – Environmental
- Water Supply and Distribution Systems
- Water and Wastewater Treatment
- Sustainable Resource Management
- Data Engineering
- Computational and Statistical Tools for Environmental Analytics
- Research Project
Through these modules, students will develop critical skills and knowledge applicable to real-world environmental challenges.
Careers with Environmental Engineering with Data ScienceGraduates of this programme can pursue diverse career paths across various sectors, including consultancy, industry, and government. Alumni have found roles in organisations focused on sustainability, resource management, and environmental protection. The programme equips students with the skills necessary for roles such as environmental consultants, data analysts in environmental sectors, and project managers in sustainability initiatives.
Programme Structure
Courses include:
- Environmental Fluid Mechanics
- Statistical Modelling
- Urban Hydrology and Urban Drainage
- Machine Learning
- Chemistry and Microbiology for Environmental Engineering
Key information
Duration
- Full-time
- 12 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
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Credits
Delivered
Campus Location
- London, United Kingdom
Disciplines
Environmental Engineering Data Science & Big Data View 65 other Masters in Environmental Engineering in United KingdomWhat students do after studying
Academic requirements
English requirements
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- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- First class Honours in civil engineering, natural sciences, earth sciences or other numerate disciplines
Tuition Fees
-
International Applies to you
Applies to youNon-residents42900 GBP / year≈ 42900 GBP / year -
Domestic Applies to you
Applies to youCitizens or residents18500 GBP / year≈ 18500 GBP / year
Living costs
London
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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Scholarships Information
Below you will find Master's scholarship opportunities for Environmental Engineering with Data Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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