Course overview
Develop technical and critical thinking skills by applying data science knowledge to real-world problems. And explore the fundamentals of big data, data visualisation and applied machine associate software tools.
You explore the professional, ethical, security and social implications of future data science technologies. And you develop the transferable skills you need to progress into industry.
- Industry links: work on live industry briefs, competitions and hackathons. Previous companies have included Cisco, Cubic Transportation Systems, Sage, TUI, Atombank, HMRC and Waterstons.
- Career-ready: our ExpoSeries allows you to showcase your skills to industry professionals who are looking to recruit new and rising talent.
- female
- black
- disabled
- from a low socioeconomic background (for example, Index of Multiple Disadvantage quintiles 1 and 2, and a low household income)
- care leaver
- estranged from parents
- Gypsy/Roma/Traveller
- refugee
- from a military family (veteran, partner of military personnel, child of military personnel).
Please note that this course is NOT suitable for students who have previously studied artificial intelligence, computer science, data science or a related subject. It is a conversion course for students who are considering a change of career or subject discipline.
Course details
Course structure
Core modules
Big Data and Data Visualisation
Businesses are increasingly seeking ways to gain intelligence to improve their bottom line and gain a competitive advantage.
Investigate the issues and technologies associated with big data analytics and data modelling. Learn how to visualise data and design impactful dashboards, identifying trends and patterns. Make business forecasts, taking informed decisions and presenting complex, multidimensional datasets in a clear and engaging form.
Data Security and Information Governance
Information security and governance are crucial elements of cyber security and business information security management systems (ISMS). Information and physical security play a crucial part in legislative compliance, ensuring high levels of privacy for accessing confidential information.
You are introduced to the principles of information security, as well as the common practices and frameworks used in industry. Consider physical and software-based technologies and how they are adopted in the real world.
Machine Learning and Deep Learning
Machine learning is a subfield of computer science concerned with computational techniques. The methodology involves building a model of a task based on observations to make predictions about unseen data.
Machine learning draws significantly from statistics and probability theory – the fundamental task is to make inferences from data samples. It’s essential to get contributions from other areas of computer science for efficient task representation, learning algorithms and inferences procedures. This module exposes you to a breadth of tasks and techniques in machine learning, investigating new developments in artificial neural networks and deep learning.
Understand the relationship between the University or workplace and your own practice in a collaborative process of knowledge generation and use. Bring together key elements of learning to demonstrate your knowledge and understanding of practice in a work-based project.
The composition, content and context of your project is unique to you. Reflect on your practice to demonstrate continual learning and development. You are taught content to help you successfully manage and complete your project.
Develop your knowledge and practical understanding of the main statistical techniques for data science. You cover both quantitative and qualitative techniques, reflecting scientific and social science methods.
Focus on correlation testing, regression, data categories, normalisation – the tools needed rather than the philosophical approaches – and how to apply valid techniques and interpret results in preparation for experimental work.
Modules offered may vary.
How you learn
You learn in group sessions that focus on practical skills supported by the academic concepts and theories. Which means you can discuss and develop your understanding of topics covered in smaller groups.
Your learning experiences are strengthened by sessions delivered by industry practitioners who share their valuable industry insights with you.
You demonstrate your computing skills that are directly related to the market. And you develop your teamworking skills, working together on solutions using the latest technologies in simulated industry setting.
Subject (or modules) are delivered in six-week blocks. You study one at a time, supported by online learning materials.
How you are assessed
It’s essential that you learn by doing. Which means that most of your assessed work is based around practical projects that you work on throughout. You get valuable tutor feedback to guide your work and your overall development.
As you progress through the course, you develop a portfolio of work - this is an important industry requirement. Our tutors can give you advice and guidance on which work to include.
And your final project allows you the freedom to set your own brief based on your skills, interests and career aspirations.
Entry requirements
You normally need to have a first degree (at least a 2.2), relevant experience or equivalent qualifications. Any subject is considered, excluding computer science, artificial intelligence and data science.
Entry from some disciplines including computing and information technology depends on course content. You need to provide a full transcript of studies for our admissions team to determine eligibility.
International students require IELTS 6.0 or equivalent.
For general information please see our overview of entry requirements.
International applicants
International applicants can find out what qualifications they need by visiting Your Country
What you need
To access the on-campus facilities you need a HTML5-capable web browser on a computer such as a Windows, Mac, Chromebook, or Linux computer. HTML5-capable web browsers that can be used include the following:
- Google Chrome
- Mozilla Firefox
- Safari
- Microsoft Edge
For some sessions you can also access sessions on the following browsers and devices:
- Chrome or Safari on an iPad (iOS 11 or later)
- Android (Android 8 or later)
- Microsoft Surface Pro (Windows 10) tablet
Don't have your own device yet?
Don't worry - we have a bank of devices available for you to loan whenever you are on campus.
You can also access Adobe Creative Cloud - a suite of 20+ world-class, industry-standard creative apps including Photoshop and InDesign.
Employability
Career opportunities
The increasing need to leverage big data has pushed so many industries to hire data scientists to predict outcomes and provide meaningful interpretations. Companies hiring data science professionals include American Express, AstraZeneca, BBC, IBM, Mastercard, Rolls Royce, Space Ape Games, Warner Bros. Entertainment, WhatsApp, and more.
As a graduate, you can expect to work in an increasing number of sectors needing specialists equipped with the cutting-edge expertise in financial and digital technologies.
You graduate prepared for a career in industry. And you have opportunities to meet and network with our industry partners through ExpoTees, our event to showcases student work to industry.
Information for international applicants
Qualifications
International applicants - find out what qualifications you need by selecting your country below.
Select your country:
Useful information
Visit our international pages for useful information for non-UK students and applicants.