Postgraduate Taught

Artificial Intelligence and Data Science

What's the difference?

computer-science-turing-lab-5
DAIM student Kuniko Azuma with lecturer
Samuel Rose outside the DAIM building
students in the SuperLab Computer Suite
viper-supercomputer
You’ll cover the full breadth of AI not just one specialism and graduate with a range of skills that put you at the forefront of data science.
This conversion course gives you the chance to switch careers and a fast-track route to a career in data science and AI.
You’ll develop programming, problem-solving, and data visualisation and interpretation skills.
You’ll be taught in our new £4.5 million DAIM facility which includes 250 of the highest-spec PCs.
Our state-of-the-art facilities include Viper – the highest-spec computer at any university in the North of England.
computer-science-turing-lab-5
DAIM student Kuniko Azuma with lecturer
Samuel Rose outside the DAIM building
students in the SuperLab Computer Suite
viper-supercomputer

The power of artificial intelligence (AI) and data science is rapidly changing our world. Be part of the next industrial revolution.

Data is one of today’s most valuable commodities. AI touches almost every walk of life – from improving diagnosis and treatment in healthcare to new creative tools for artists.

The need for skilled graduates who understand the full breadth of the technology is greater now than ever before.

  • Switch careers

    with this Masters conversion

  • Work while you study

    with intensive teaching

  • State-of-the-art-facilities

    in our £4.5 million DAIM centre

  • Get up to £10,000

    towards your tuition fees 1

  • Graduate at the forefront

    of data science

Swipe
Course overview
Module options

About this course

Want to change direction? Switch careers? Upskill? This fast-track Masters is for you.

Taught in our £4.5 million Centre of Excellence for Data Science, Artificial Intelligence and Modelling (DAIM), our MSc offers a fast-track to career success in this dynamic field.

As a conversion course, this MSc is suitable for students with a range of backgrounds in STEM and non-STEM subjects. With intensive teaching – your in-person lectures and workshops will normally be on one day a week 9am to 6pm – so you can balance your studies alongside other commitments, too.

Don’t have programming experience? That’s okay. You’ll learn Python coding at the start of the course to make sure you’re up to speed.

Unlike other universities, you’ll study the full breadth of AI – not just one specialism. You’ll cover programming, statistics, machine learning, big data, data visualisation, computer vision and the ethical and legal responsibilities of using data.

You can design your own research project to suit your background and career interests. Some students may be able to with work on a research project with one of our industry partners such as Naimuri, the NHS, KCOM or Lampada Digital Solutions.

You’ll develop key skills including programming, problem-solving, and data visualisation and interpretation. And graduate at the forefront of data science.

Choose your modules

Unlike other universities, you’ll cover the full breadth of AI – not just one specialism. From programming and machine learning, to big data and ethical responsibilities. In trimester one you’ll take an AI and a data science module, together with the programming module. In trimester two, you’ll advance your AI and data science skills with further modules.

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

Fundamentals of Data Science

An introduction to the principles of data science and data analysis. Topics include:      

  • Data Science Context: Datafication of society and the history of data science.
  • Properties and types of data (e.g., quantitative and categorical data)
  • Classification and regression, introduction to Kaggle and other sources of data
  • Data Management: Data collection and techniques; Cleaning of data and processing; Data errors and artefacts; missing data
  • Introductory statistical approaches to data: Basic mathematical concepts; Introduction to probabilities; Descriptive statistics (e.g., centrality measures) and characterizing distributions; Correlations; Statistical hypothesis testing
  • Data analysis and visualization: Types of visualization and interpretation; Identifying outliers; Regression models
  • Applications: Real-world data applications, including examples

   This module is assessed by a presentation and project report. 

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

Big Data and Data Mining

The module will build on the concepts introduced in the first data science module and introduce Big Data and Data Mining, including network analysis. Topics will include:      

  • Databases, including the use of the SQL language.
  • Association Pattern Data Mining: the Brute force approaches and A priori algorithm.
  • Sorting Algorithms: Bubble sort
  • Clustering: DBSCAN
  • Time series analysis: ARIMA: XGBOOST
  • Web Scraping/spidering: Beautiful Soup; Legal and ethical aspects
  • Network Analysis: social media, graph theory, network visualisation and similarity measures

This module is assessed by a presentation and a project 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

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•20 credits

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 

•20 credits

Fundamentals of Data Science

An introduction to the principles of data science and data analysis. Topics include:      

  • Data Science Context: Datafication of society and the history of data science.
  • Properties and types of data (e.g., quantitative and categorical data)
  • Classification and regression, introduction to Kaggle and other sources of data
  • Data Management: Data collection and techniques; Cleaning of data and processing; Data errors and artefacts; missing data
  • Introductory statistical approaches to data: Basic mathematical concepts; Introduction to probabilities; Descriptive statistics (e.g., centrality measures) and characterizing distributions; Correlations; Statistical hypothesis testing
  • Data analysis and visualization: Types of visualization and interpretation; Identifying outliers; Regression models
  • Applications: Real-world data applications, including examples

   This module is assessed by a presentation and project report. 

•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.  

•20 credits

Big Data and Data Mining

The module will build on the concepts introduced in the first data science module and introduce Big Data and Data Mining, including network analysis. Topics will include:      

  • Databases, including the use of the SQL language.
  • Association Pattern Data Mining: the Brute force approaches and A priori algorithm.
  • Sorting Algorithms: Bubble sort
  • Clustering: DBSCAN
  • Time series analysis: ARIMA: XGBOOST
  • Web Scraping/spidering: Beautiful Soup; Legal and ethical aspects
  • Network Analysis: social media, graph theory, network visualisation and similarity measures

This module is assessed by a presentation and a project report.   

•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

•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.

•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.

•20 credits
14 Modules

Our academics

You’ll be taught in DAIM – a centre of excellence created for this course, drawing on expertise from across the University.

Our academics’ broad specialisms include computer science, machine learning, AI, astrophysics, mathematics earth sciences, geospatial, music, engineering, ethics and medicine.

See more academics for this subject
Dr Kevin Pimbblet
Featured academic

Dr Kevin Pimbblet

Kevin is an experienced British-Australian observational astronomer and the Director of DAIM. His research covers modern astrophysical topics and issues in areas including cosmology, extra-galactic astronomy and large-scale structure of the Universe.

Entry requirements

What do I need?

Typical offer
2:1 in relevant subject area

Your degree should have strong numerical content.

Additional entry requirements for this course

You will also need to have previously studied a course or module in mathematics (pure or applied), statistics, computing, or data analysis.

You’ll need a personal statement outlining the above, plus your eligibility for our £10,000 bursary if you’re applying for this.

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.

What do I need?

Typical offer
2:1 in relevant subject area

Your degree should have strong numerical content.

Additional entry requirements for this course

You will also need to have previously studied a course or module in mathematics (pure or applied), statistics, computing, or data analysis.

You’ll need a personal statement outlining the above, plus your eligibility for our £10,000 bursary if you’re applying for this.

If you require a student visa to study or if your first language is not English you will be required to provide acceptable evidence of your English language proficiency level.

This course requires academic IELTS 6.5 overall, with no less than 6.0 in each skill. See other English language proficiency qualifications accepted by the University of Hull.

If your English currently does not reach the University’s required standard for this programme, you may be interested in one of our English language courses.

Visit your country page to find out more about our entry requirements.

Fees & funding

How much is it?

Additional costs you may have to pay

Your tuition fees will cover most costs associated with your programme. There are some extra costs that you might have to pay, or choose to pay, depending on your programme of study and the decisions you make:

  • Books (you can borrow books on your reading lists from the library, but you may buy your own)
  • Optional field trips
  • Study abroad (incl. travel costs, accommodation, visas, immunisation)
  • Placement costs (incl. travel costs and accommodation)
  • Student visas (international students)
  • Laptop (you’ll have access to laptops and PCs on campus, but you may want your own)
  • Printing and photocopying
  • Professional-body membership
  • Graduation (gown hire and photography)

Remember, you’ll still need to take into account your living costs. This could include accommodation, travel, food and more.

How do I pay for it?

How much is it?

Additional costs you may have to pay

Your tuition fees will cover most costs associated with your programme. There are some extra costs that you might have to pay, or choose to pay, depending on your programme of study and the decisions you make:

  • Books (you can borrow books on your reading lists from the library, but you may buy your own)
  • Optional field trips
  • Study abroad (incl. travel costs, accommodation, visas, immunisation)
  • Placement costs (incl. travel costs and accommodation)
  • Student visas (international students)
  • Laptop (you’ll have access to laptops and PCs on campus, but you may want your own)
  • Printing and photocopying
  • Professional-body membership
  • Graduation (gown hire and photography)

Remember, you’ll still need to take into account your living costs. This could include accommodation, travel, food and more.

How do I pay for it?

Our 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.

Find out more about our scholarships

Artificial Intelligence and Data Science Bursaries

These bursaries, worth £10,000 each, are designed to help support widening participation students study MSc Artificial Intelligence and Data Science.

Find out more and see if you’re eligible.

Alumni Postgraduate Scholarship

University of Hull undergraduates progressing to a taught masters course may receive a 25% discount on the cost of their tuition fees.

Find out if you’re eligible by visiting the University of Hull Alumni Postgraduate Scholarship page.

International Scholarships and Bursaries

We offer a range of scholarships and bursaries for international students.

To find out more and see if you're eligible, please visit the International Scholarships and Bursaries page.

Take a look at our facilities

DAIM

You’ll find 250 of the highest-spec PCs in this new, state-of-the-art facility where you’ll learn, practice and apply your coding, programming, AI and data science skills.

Supercomputing

You’ll have access to Viper – the highest-spec computer at any university in the North of England.

Superlab

Fully refurbished as part of a significant investment in high-performance workstations, servers and social spaces, our Superlab is also open to students outside of teaching hours.

Brynmor Jones Library

Our seven-storey library is a superb learning space. As well as more than a million books, there’s a variety of study areas, over 400 open-access PCs and one amazing view.

See more in our virtual tour
DAIM building exterior
VIPER high performance computing
students in the SuperLab Computer Suite

Look around

DAIM building exterior
VIPER high performance computing
students in the SuperLab Computer Suite
Brynmor Jones Library Observation Deck
James Gordon, Computer Science

Future prospects

There’s a shortage of qualified data practitioners to meet the growing needs of employers. So you’ll be in high demand.

You’ll graduate the ability to apply AI and data science techniques to real-world problems. And could go on to work as a data scientist in a wide range of industries. Our recent graduates have joined big names such as Amazon and Scottish Power

You’ll also be able to critically evaluate AI and data science methodologies. Plan, design and carry out empirical research. And interpret, present and communicate the outcomes of data science and AI solutions. Which means you’ll be ready to progress to further study in a broad variety of subjects.

University of Hull Open Day

Your next steps

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.

Apply now
How to apply

Not ready to apply?

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.

Discover more

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  1. The University has been awarded Government funding to provide a limited number of scholarships of £10,000 each to support students from underrepresented groups. 

    Find out more and check if you’re eligible.

All modules presented on this course page are subject to availability and this list may change at any time.

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