Applied Data Science (Ecology and Evolution) MSc

Program Overview

The MSc Applied Data Science (Ecology and Evolution) is a one-year, full-time program that immerses students in data-driven approaches to ecology, evolution, conservation, biodiversity, and epidemiology. Through a blend of coursework, workshops, and a research project, students develop skills in data analysis, modeling, and communication, preparing them for careers as data scientists, environmental consultants, research scientists, and policy analysts. The program is unique in its emphasis on interdisciplinary collaboration and opportunities to work on real-world projects.

Program Outline

Degree Overview:

• Objectives: Develop expertise in data-driven perspectives on ecology, evolution, conservation, biodiversity, and epidemiology.
• Program Description:
• Immerse students in the "Big Data revolution" and equip them with the skills to analyze and interpret data in the fields of ecology and evolution.
• Provide a strong foundation in data science and its applications in the life sciences.
• Offer opportunities to work with industry, charities, or the public sector.
• Develop expertise in data-driven perspectives on ecology, evolution, conservation, biodiversity, and epidemiology.
• Gain the skills and experience needed to succeed in the demanding and fast-growing data analytics sectors, particularly in relation to ecology and evolution.

Outline:

• Program Structure:
• Full-time, 1-year program.
• Delivered at the Penryn Campus in Cornwall.
• Course Schedule:
• Term 1:
Focus on core skills and understanding through fundamental modules in data science and ecology and evolution.
• Term 2: Exposure to state-of-the-art methods in the "Trends in Data Science and Artificial Intelligence" module, completion of the interdisciplinary, inquiry-led module "Tackling Sustainability Challenges using Data and Models," and the option to select further Masters level modules within biosciences.
• Term 3: Undertaking an advanced data science and modeling project.
• Modules:
• Term 1:
• Fundamentals of Data Science:
Covers the core principles and techniques of data science, including data collection, cleaning, analysis, and visualization.
• Ecology and Evolution: Provides a comprehensive overview of ecological and evolutionary principles, including population dynamics, community ecology, and evolutionary processes.
• Term 3:
• Advanced Data Science and Modelling Project:
Students undertake an independent research project, applying their data science skills to a specific problem in ecology or evolution.

Assessment:

• Assessment Methods:
• The program utilizes a variety of assessment methods, including:
• Exams:
To assess students' understanding of core concepts and principles.
• Assignments: To demonstrate students' ability to apply their knowledge and skills to real-world problems.
• Presentations: To develop students' communication and presentation skills.
• Project: To showcase students' independent research abilities and data analysis skills.
• Assessment Criteria:
• The assessment criteria will vary depending on the specific module and assessment method.
However, general criteria may include:
• Application: Applying knowledge and skills to solve problems and answer questions.
• Analysis: Critically analyzing data and drawing conclusions.
• Communication: Communicating findings effectively in written and oral formats.

Teaching:

• Teaching Methods:
• The program employs a variety of teaching methods, including:
• Lectures:
To deliver core concepts and principles.
• Seminars: To engage in discussions and debates.
• Workshops: To develop practical skills and techniques.
• Faculty:
• The program is taught by experts in data science, ecology, and evolution.
• Faculty members are actively involved in research and have a strong track record of publishing in leading journals.
• Unique Approaches:
• The program emphasizes an interdisciplinary approach, integrating data science with ecological and evolutionary principles.
• Students have the opportunity to work on real-world projects with industry, charities, or the public sector.

Careers:

• Potential Career Paths:
• Data Scientist:
Analyze and interpret data to solve problems in ecology, evolution, conservation, biodiversity, and epidemiology.
• Environmental Consultant: Provide expert advice on environmental issues, using data science to inform decision-making.
• Research Scientist: Conduct research in ecology, evolution, or related fields, using data science to analyze and interpret data.
• Policy Analyst: Develop and implement policies related to environmental issues, using data science to inform decision-making.
• Opportunities:
• The UK has a strong and growing data analytics sector, with high demand for qualified professionals.
• The program provides students with the skills and experience needed to succeed in this competitive field.
• The program also prepares students for careers in research, consulting, and policy.
• Outcomes:
• Graduates of the program will be equipped with the skills and knowledge to pursue a successful career in data science, ecology, evolution, or related fields.
• They will be able to analyze and interpret data, solve problems, and communicate their findings effectively.
• They will be well-prepared to contribute to the advancement of knowledge and the development of solutions to environmental challenges.

Other:

• Research: The program is led by the Centre for Environmental Mathematics and taught in collaboration with the Centre for Ecology and Conservation (CEC).
Students have access to the latest research facilities and opportunities to participate in ongoing research projects.
• Graduate School of Environment and Sustainability: Students become part of Exeter's Graduate School of Environment & Sustainability, a vibrant and supportive postgraduate community based at the Penryn campus.
This provides opportunities for interdisciplinary learning and networking with other students and faculty.
• Career Zone: Students receive support from the Career Zone team, which provides career guidance, training events, workshops, and connections with industry professionals.

2024/25 entry UK fees per year: £12,100 full-time International fees per year: £27,500 full-time