STUDY

Postgraduate

MSc Data Science and Artificial Intelligence

Green data/particle wave
Institution code: S82
UCAS code: N/A
Start date: September 2024
Duration: One year full-time, two years part-time
Location: Ipswich
Typical Offer: 2:2 or above in an undergraduate degree.
Institution code: S82
UCAS code: N/A
Start date: September 2024
Duration: One year full-time, two years part-time
Location: Ipswich
Typical Offer: 2:2 or above in an undergraduate degree.

Overview

The MSc Data Science and Artificial Intelligence is a postgraduate conversion degree. It is a partnership between us and you – we will give you the opportunities to gain deep knowledge, practical skills and meaningful expertise in data science and artificial intelligence, you bring enthusiasm, determination and a willingness to learn and make the most of the opportunities.

The University of Suffolk is an accredited AWS Academy, allowing students on the MSc Data Science and Artificial Intelligence degree to be taught the AWS Academy cloud computing curriculum by approved AWS Educators. 

This is a conversion course so your undergraduate degree can be in any subject.

The University of Suffolk is world-class and committed to our region. We are proudly modern and innovative and we believe in transformative education. We are on the rise with a focus on student satisfaction, graduate prospects, spending on academic services and student facilities.

2nd

in the East of England for graduate prospects

(The Complete University Guide 2024)

6th

in the UK for spend on academic services

(The Complete University Guide 2024)

11th

in the UK for social inclusion

(The Good University Guide 2023)

Course Modules

Full downloadable information regarding all University of Suffolk courses, including Key Facts, Course Aims, Course Structure and Assessment, is available in the Definitive Course Record.

This module provides an introduction to the artificial intelligence field, covering the history of the discipline and exploring the breadth of the discipline from “classical AI” to the current forefront areas. It provides a grounding in how to undertake research in AI and data science, and considers ethical issues arising in AI and data science applications.

Programming is a core skill throughout computing. This module will cover Python programming with particular emphasis on using Python to solve problems with AI and data science techniques. No programming experience will be assumed. The module will begin with the key elements of Python programming and build towards harnessing the standard Python libraries and packages to create solutions. Best practices of Python coding will be embedded throughout the module. The module will also provide a primer on software engineering of solutions, with an emphasis on the importance of testing.

Industry, commerce and research are being transformed by the potential to capture, store, manipulate, analyse and visualise data and information on a massive scale. Relational (SQL) databases and data warehouses remain important repositories of information to many organisations. The advent of Big Data with its variety, velocity and volume has challenged relational databases, leading to the emergence of NoSQL databases. Yet the query languages of NoSQL databases have evolved closer to SQL capabilities. This module will cover both SQL and NoSQL approaches to data modelling, database design and manipulation, so that you can use the right tool for the right job.

Data science and artificial intelligence includes many techniques for classification, analysis and prediction. This module focuses on those techniques relating to data mining and statistically driven approaches, providing you with an arsenal of methods to solve business problems and generate real insights. 

Deep learning is central to modern AI. A sufficiency of inexpensive computing power, sufficiently large datasets and a number of key theoretical advances created deep learning techniques which have facilitated a wave of accuracy increases across many computational tasks (computer vision, natural language processing, speech recognition, autonomous driving, etc.), making many applications practical. This module explains the underlying mathematics and techniques, so that you can master deep learning and solve real problems.

The on-demand delivery of compute, database, storage, applications and IT resources through cloud computing has enabled many organisations to deliver innovative solutions without upfront capital investment. Cloud computing ecosystems provide a variety of scalable AI and machine learning solutions. This module provides a comprehensive grounding in cloud computing concepts and solutions, buttressed with extensive practicals to build experience in individual services and architectural designs. As the University of Suffolk is an AWS Academy partner institution, the module will give you an opportunity to acquire AWS certification(s) if you so wish. 

The Masters Project is the culmination of our taught MSc degrees. This project is your opportunity to apply the knowledge and skills acquired from all the earlier modules on a real task – it is very likely a project proposed by a company or research organisation.

Course Modules 2024

Full downloadable information regarding all University of Suffolk courses, including Key Facts, Course Aims, Course Structure and Assessment, is available in the Definitive Course Record.

This module provides an introduction to the artificial intelligence field, covering the history of the discipline and exploring the breadth of the discipline from “classical AI” to the current forefront areas. It provides a grounding in how to undertake research in AI and data science, and considers ethical issues arising in AI and data science applications.

Programming is a core skill throughout computing. This module will cover Python programming with particular emphasis on using Python to solve problems with AI and data science techniques. No programming experience will be assumed. The module will begin with the key elements of Python programming and build towards harnessing the standard Python libraries and packages to create solutions. Best practices of Python coding will be embedded throughout the module. The module will also provide a primer on software engineering of solutions, with an emphasis on the importance of testing.

Industry, commerce and research are being transformed by the potential to capture, store, manipulate, analyse and visualise data and information on a massive scale. Relational (SQL) databases and data warehouses remain important repositories of information to many organisations. The advent of Big Data with its variety, velocity and volume has challenged relational databases, leading to the emergence of NoSQL databases. Yet the query languages of NoSQL databases have evolved closer to SQL capabilities. This module will cover both SQL and NoSQL approaches to data modelling, database design and manipulation, so that you can use the right tool for the right job.

Data science and artificial intelligence includes many techniques for classification, analysis and prediction. This module focuses on those techniques relating to data mining and statistically driven approaches, providing you with an arsenal of methods to solve business problems and generate real insights. 

Deep learning is central to modern AI. A sufficiency of inexpensive computing power, sufficiently large datasets and a number of key theoretical advances created deep learning techniques which have facilitated a wave of accuracy increases across many computational tasks (computer vision, natural language processing, speech recognition, autonomous driving, etc.), making many applications practical. This module explains the underlying mathematics and techniques, so that you can master deep learning and solve real problems.

The on-demand delivery of compute, database, storage, applications and IT resources through cloud computing has enabled many organisations to deliver innovative solutions without upfront capital investment. Cloud computing ecosystems provide a variety of scalable AI and machine learning solutions. This module provides a comprehensive grounding in cloud computing concepts and solutions, buttressed with extensive practicals to build experience in individual services and architectural designs. As the University of Suffolk is an AWS Academy partner institution, the module will give you an opportunity to acquire AWS certification(s) if you so wish. 

The Masters Project is the culmination of our taught MSc degrees. This project is your opportunity to apply the knowledge and skills acquired from all the earlier modules on a real task – it is very likely a project proposed by a company or research organisation.

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WHY SUFFOLK

16th place in the Whatuni Student Choice Awards for Best Facilities 2023

WUSCA 2023

5th place in the Whatuni Student Choice Awards for Career Prospects 2023

WUSCA 2023

14th place in the Whatuni Student Choice Awards for Student Support 2023

WUSCA 2023
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Student at The DigiTech Centre
Three students gaming in classroom
Students at The DigiTech Centre
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Students at The DigiTech Centre
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Inside The DigiTech Centre

Entry Requirements

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Career Opportunities

Employer demand for people skilled in Data Science and AI is proven. The number of AI jobs in the UK listed on its online jobs board grew 485% between 2014 and 2017 according to research from the job website ‘Indeed’. Gartner’s survey on AI revealed that there is a rapid growth in the number of AI based jobs in big organisations, and a tempo change from 4 projects per organisation in 2019 to 10 projects in 2020 and accelerating to an expected 35 projects in 2022.  
 
Regionally digital skills in general and Data Science in particular have been identified by employers as a priority area. The Innovation Martlesham cluster where the University of Suffolk’s new DigiTech Centre is co-located has seen growth in the number of ICT jobs from 600 in 2016 to 1200 in 2019 with 2000 jobs projected for 2024.

An increasing percentage of these jobs require core skills in Data Science and AI. Consultations with regional businesses revealed that there is an increasing demand for professionals with strong Data Science skills who are capable of developing machine learning models based on existing AI rapid development frameworks. As a graduate of this degree, you will be ideally placed to take advantage. 
 
In addition to careers in industry, as a graduate of this course, you will also be able to progress into doctoral research. 

Your Course Team

Dr Adnane Ez-zizi

Dr Adnane Ez-zizi is a Senior Lecturer in Artificial Intelligence and Course Leader for the MSc Data Science and Artificial Intelligence.

Adnane Ez-Zizi staff profile photo

Dr Kakia Chatsiou

Kakia is a Lecturer in Computing with expertise in machine learning, information management systems and data science.

Kakia Chatsiou staff profile photo

Hisham Jaward

Hisham is a lecturer in Computing and AI. Work at previous universities in Monash, Bristol and Imperial College, UK, have included developing algorithms.

Hisham Jaward staff profile photo

Steven Harris

Steve maintains an active interest in 'serious games' including, gaming for the visually impaired and early years educational games.

Steven Harris staff profile photo

Fees and Funding

UK Full-time Tuition Fee

£9,495

per year
UK Part-time Tuition Fee

£1,097*

per 20 credit module
International Full-time Tuition Fee

£15,300

per year

*Please contact the Student Centre for further details

Further Information

Postgraduate Loans are available for this course, we also offer University of Suffolk Alumni a 25% reduction on fees, find out more below.

Postgraduate Funding Alumni Loyalty Scheme International Students

How to apply

Applying for a postgraduate programme is simple, you can apply using the link below. You can also find out more about what to include on your application and how to contact us for support during the process on the Postgraduate Study link.

Apply Now Postgraduate Study
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"The University of Suffolk empowered me to be better, to aim high and to make positive changes. I found people here that inspired me and supported me through my journey."

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