Artificial intelligence (AI) and data science are revolutionising geospatial data analysis, reshaping how we understand and interact with our environment. Be at the forefront of this transformative field.
In today’s data-driven world, geospatial data is incredibly powerful. AI is making a significant impact by enabling more precise environmental monitoring, enhancing urban planning, and optimising resource management.
The demand for skilled graduates who can harness the full potential of AI in geospatial data analysis has never been higher.
About this course
Geospatial analysis is being radically changed by embedding data science and data analytics into the discipline. Rather than a human being looking at data and images of the Earth, artificial intelligence is being increasingly deployed to automate tasks that humans cannot otherwise accomplish in any reasonable amount of time. Nationally, there is a widely recognised shortage of qualified Artificial Intelligence (AI) and data scientists to meet the needs of industry. This course will equip you with the skills and professional insight needed to launch a career in this fast-growing sector.
As a conversion degree, you do not need a science background. And the knowledge you gain will help you build a portfolio that will launch you into the field of data science, acquiring highly sought after skills that will greatly enhance your career pathway. The programme will cover topics such as, programming, statistics, machine learning, data visualisation and computer vision and the ethical and legal responsibilities of using data. This geospatial data analysis variant will include bespoke modules covering the fundamentals of geo-information science and earth observation, and spatio-temporal big data analytics.
In the third semester, you will have the opportunity to choose or design your own research project in a disciplinary area which may relate to your background or career goals. Alternatively, there may also be opportunity to undertake a project working with an industry partner.
Module options
For a full Masters degree, you'll study 180 credits over the duration of your course. Some programmes offer a Postgraduate Diploma (PGDip) qualification or a Postgraduate Certificate (PGCert) qualification. For a PGDip, you'll study 120 credits, and for a PGCert, you'll study 60 credits.
Filters
Programming for AI and Data Science
Learn the fundamentals of Python coding so you can progress onto the rest of the course.
Assessment: Portfolio of work
core
20 credits
Understanding Artificial Intelligence
An introduction to the fundamental concepts in Artificial Intelligence, and their application. Topics include:
- Origins of AI: What is AI? From early history to the Dartmouth conference and the present day; Intelligent agents, and performance measures
- Learning, Frameworks and Packages: Introduction to supervised learning; Regression; Classification; Clustering; Artificial Neural Networks; Convolutional Neural Networks; Keras; Tensorflow
- Implications for Society: Legalities; Ethics and professional implications; Social consequences
This module is assessed by a portfolio of work, in the form of a programmed code and a corresponding technical report.
core
20 credits
Applied Artificial Intelligence
The module will build on the concepts introduced in the first AI module, and prepare you for your dissertation. Topics include classification revisited, deep learning, applications to problems, cognitive bias, and implications for equality.
Assessment: Presentation and project report
core
20 credits
Research and Application in Artificial Intelligence and Data Science
The module contains two themes that are strongly interrelated to each other:
The first theme offers options to study how AI and Data Science apply to real-world contexts. Options could include sustainability, healthcare, social responsibility, the creative industries, and the natural environment.
Alongside the first theme, you’ll develop your own research proposal to tackle a genuine research project. You’ll draw from the experiences in the options to identify questions and limitations associated with your proposed research. This will prepare you for your dissertation in Trimester 3.
core
20 credits
Fundamentals of Geospatial Data and Earth Observation
In this module you will learn the underlying theory and a range of practical applications of geo-information science and earth observation. You will examine how we use different types of geospatial data to understand environmental processes and how they are affected by humans.
core
20 credits
Artificial Intelligence and Data Science Research Project
Plan and work independently on your own complex research-based problem. And report on the aims, methods and outcomes of your scientific investigation.
core
59 credits
Spatio-temporal Big Data Analytics
In this module you will delve into the fundamental principles and advanced practical uses of spatial and temporal big data. You will explore the utilization of various spatial and temporal analytics strategies to comprehend urban challenges (e.g., transport, mobility and security) and solve real-world problems effectively.
core
20 credits
Our academics
You’ll be taught in DAIM – a centre of excellence created for this course, drawing on expertise from across the whole University.
Our course is taught by experts in Artificial Intelligence and data science with backgrounds in geospatial analysis, earth observation, geology and more, as well as highly-cited researchers and brilliant teachers with fellowships of Advanced HE. You'll experience hands-on learning in our 4.5million GBP teaching facility.
Kevin Pimbblet
Director of DAIM; Professor
Kevin is an experienced British-Australian observational astronomer and applied data scientist, having worked in multiple research intensive institutions across two continents. His core research interests cover a number of astrophysical topics.
Ruben Valcarce Dineiro
Lecturer in Geospatial and Earth Observation
Lecturer in Geospatial and Earth Observation with several years of experience in the private sector working on methods development for different applications using remotely sensed datasets.
Entry Requirements
What do I need?
When it comes to applying for this Postgraduate Taught degree, you'll need an Undergraduate degree (or equivalent). For this course, you'll need a 2:2 from a relevant bachelor's degree.
The programme is designed for graduates who have a studied a subject that is relevant to this course.
If you’re an undergraduate student at Hull, you’re guaranteed a fast-track route to this postgraduate degree, as long as you meet the entry requirements.
In order to ensure our students have a rich learning and student experience, most of our programmes have a mix of domestic and international students. We reserve the right to close applications early to either group if application volumes suggest that this blend cannot be achieved.
Typical offer
2:2 in a relevant subject area
Applicants will require a 2:2 undergraduate honours degree in any subject that includes a numerical component (i.e. statistical analysis, or formal mathematics, or programming in any given language), or equivalent industrial experience.
Fees & Funding
How much is it?
Scholarships
We offer a number of awards, bursaries and scholarships for eligible students. They’re awarded for a variety of reasons including academic achievement and/or to help those on lower incomes.
Scholarships and bursaries are separate to student loans. And the best bit is, you don’t pay a penny back
Alumni Postgraduate Scholarship
University of Hull undergraduates progressing to a taught masters course may receive a 20% discount on the cost of their tuition fees.
Find out if you’re eligible by visiting the University of Hull Alumni Postgraduate Scholarship page.
See more Scholarships
We offer a range of scholarships and awards to students at the university to help with their financial load.
To view all of our scholarships and determine whether you're eligible, please visit our Scholarships and Awards page.
Artificial Intelligence Facilities
Future prospects
There's an increasing demand for skilled professionals who can apply AI in geospatial data analysis, making your expertise highly valuable to employers. You'll be in high demand.
Upon graduation, you'll possess the skills to leverage AI and data science techniques to address real-world challenges in geospatial analysis. You’ll also gain the ability to critically evaluate AI and data methodologies, design and conduct empirical research, and effectively interpret, present, and communicate AI-driven solutions. This expertise can open doors to advanced careers such as Remote Sensing Scientist, Earth Observation Scientist, Geospatial Analyst, Data Engineer, or Consultant across various geospatial industries.
Take your career to the next level
Like what you’ve seen? Then it’s time to apply.
Make your application online now, and our admissions team will get back to you as soon as possible to make you an offer.
Not ready to apply yet?
We regularly deliver virtual and on-campus events to help you discover your perfect postgraduate course, whether it’s a subject you already love or something completely different. Our events are an opportunity for you to chat to tutors and current students and find out about the career options a postgraduate degree could lead to.