Environmental Data Science MSc, PGDip
| Program start date | Application deadline |
| 2025-09-01 | - |
Program Overview
Environmental Data Science MSc, PGDip
Course Description
The MSc in Environmental Data Science is an interdisciplinary program that equips students with the skills to manipulate, analyze, model, and visualize environmental data. The program addresses the shortage of qualified data scientists in the UK and abroad, providing students with a broad range of fundamental data science techniques.
Entry Requirements
- Students are required to have a second-class honors degree in any subject.
- Students with non-standard qualifications are encouraged to apply.
- Prior professional experience gained by mature students in relevant areas of work will be considered.
- IELTS 6.5 or equivalent is required for international students.
Fees and Funding
- UK Students:
- MSc: £10,950
- MSc with Industry: £10,950
- PGDip: £7,295
- International Students:
- MSc: £23,650
- MSc with Industry: £23,650
- PGDip: £15,750
- An additional fee of £3,520 will be charged if a placement is secured.
Careers and Employability
The program furnishes students with technical and transferable skills, enabling them to pursue careers as Environmental Data Scientists/Analysts/Consultants in various businesses, consultancies, governments, and research institutions.
Related Courses
- Environmental Futures MSc
- Geographical Data Science MSc
- Satellite Data Science MSc
Course Structure
Core Modules
- Introduction to Environmental Modelling
- Overview of Data Science Practice
- Statistics for Data Science
- Fundamentals of Data Science
- Applications of Environmental Modelling
- Research for Change: Skills and Challenges of Applied Environmental Research
- Dissertation
Option Modules
- Geospatial Data Analytics
- Geographical Artificial Intelligence
- Field Data Capture
- Information Visualisation
- Overview of Data Science Practice
'With Industry' Option
The 'With Industry' variant of this degree gives students the opportunity to take an Industrial Placement as part of their Masters. This is a work placement with an employer where students develop their skills in a 'real-world' setting.
Teaching and Learning
The program is taught using a range of methods, including lectures, seminars, practical classes, workshops, tutorials, project supervision, and fieldwork. The program includes a blend of assessment, including traditional and authentic assessment types.
Why Leicester?
The program is accessible to students without a strong computing or mathematical background. Transferable data science skills are explicitly taught and developed within strong disciplinary and vocational contexts. The program is taught by staff with international reputations as researchers and consultants to businesses and government agencies. NA
Program Outline
Environmental Data Science MSc, PGDip - Detailed Extraction
Degree Overview:
This MSc program in Environmental Data Science equips students with the skills needed to understand and model natural systems, ultimately contributing to solving pressing environmental issues. The program focuses on developing data manipulation, analysis, modeling, and visualization skills, enabling students to find patterns and trends in datasets and uncover new insights. The program addresses the growing demand for expertise in Data Science within the environmental field, offering a strong foundation for a career in this area.
Objectives:
- Develop strong data manipulation, analysis, modeling, and visualization skills.
- Gain a deeper understanding of environmental processes.
- Inform societal action and sustainable decision-making.
- Address the shortage of qualified data scientists in the UK and abroad.
- Prepare students for a successful career in data science.
Outline:
Core Modules:
- Introduction to Environmental Modelling: This module provides an overview of environmental modeling techniques and their applications.
- Overview of Data Science Practice: This module introduces fundamental concepts and practices in data science, covering topics like data collection, cleaning, and preparation.
- Statistics for Data Science: This module focuses on statistical methods relevant to data science, including hypothesis testing, regression analysis, and machine learning.
- Data Science for Actuaries: This module explores the application of data science techniques in the actuarial field, focusing on risk assessment and financial modeling.
- Applications of Environmental Modelling: This module delves into practical applications of environmental modeling in various fields, such as climate change, pollution, and resource management.
- Research for Change: Skills and Challenges of Applied Environmental Research: This module equips students with the skills and knowledge needed to conduct impactful environmental research, focusing on ethical considerations and real-world applications.
Option Modules:
- Geospatial Data Analytics: This module explores the use of geospatial data in environmental analysis, covering topics like remote sensing, GIS, and spatial statistics.
- Geographical Artificial Intelligence: This module focuses on the application of artificial intelligence techniques in geography, including machine learning, deep learning, and computer vision.
- Field Data Capture: This module provides practical training in data collection methods, including field sampling, sensor deployment, and data logging.
'With Industry' Option:
This variant of the degree offers students the opportunity to gain practical experience through an industrial placement. Placements typically last between 3 and 12 months and are paid, full-time positions with a formal contract. The placement provides students with real-world experience in a company setting, allowing them to develop hands-on skills and gain valuable insights into their chosen career path.
Assessment:
The program utilizes a blend of assessment methods, including:
- Traditional assessments: Essays and examinations.
- Authentic assessments: Problem-based tasks based on real-world scenarios and datasets. The emphasis is placed on coursework rather than end-of-module examinations, allowing students to demonstrate their knowledge and understanding in real-world contexts using a wide range of transferable skills.
Teaching:
The program is taught using a variety of methods, including:
- Lectures
- Seminars
- Practical classes and workshops
- Tutorials
- Project supervision
- Fieldwork The program is taught by staff with international reputations as researchers and consultants to businesses and government agencies. These faculty members are actively engaged in tackling a wide range of globally important environmental problems and contribute to policy debates of national and international significance.
Careers:
Graduates of this program are highly employable as Environmental Data Scientists/Analysts/Consultants in a range of businesses, consultancies, governments, and research institutions. These roles involve using environmental data to better understand and manage the natural world, human societies, and their inter-relationships and interactions.
Other:
- The program is accessible to students without a strong computing or mathematical background.
- Transferable data science skills are explicitly taught and developed within strong disciplinary and vocational contexts.
- Students taking the 'with industry' version of the degree can seek placements with a range of commercial organizations associated with environmental and data science sectors of the economy.
Note:
The program's specific content, structure, and assessment methods may change in future years.
UK Students
Starting in September 2024 MSc: £10,700 PGDip: £7,125 If you are resident outside the UK and the Republic of Ireland, you will need to pay a deposit of £3,000 to secure your place. This will be subtracted from your total tuition fee.
International Students
Starting in September 2024 MSc: £23,650 PGDip: £15,750 You will need to pay a deposit of £3,000 to secure your place. This will be subtracted from your total tuition fee.
