Advanced Data Science

• Develop advanced skills in statistical analysis, business analytics, data processing, and natural language processing, including large language models (LLMs)
  
• Gain a critical understanding of the principles, methods and challenges of modern data science, including ethics, trust, and governance in AI systems
• Learn the latest techniques and tools delivered by research-active academics with expertise in data science, artificial intelligence, and real-world analytics
• Build the ability to apply analytical and computational methods to real-world datasets across business, public services, engineering, and digital industries
• Develop independent research and problem-solving skills through a substantial MSc project

Future focused content

Organisations across every sector are increasingly driven by data. The ability to extract insight, build predictive models, and communicate results effectively is now a core professional skill. This programme provides a robust grounding in statistics, data analytics, and large-scale data processing, combined with a strong emphasis on practical application and responsible AI.

You will study key areas of advanced data science including: 

• statistical techniques for data analysis and modelling 

• business and organisational analytics 

• processing and analysing large and complex datasets 

• natural language processing and text analytics 

• ethics, trust, and governance in data and AI systems 

• research methods and independent scholarship

The programme has been developed in collaboration with industry partners that are global leaders in data and AI solutions, whose platforms are widely used across industry and academia. You will gain both theoretical knowledge and hands-on experience with modern analytics software and tools, preparing you for careers in data science, analytics, and artificial intelligence. 

You will also have the opportunity to work towards an industry-recognised SAS qualification by taking the relevant professional examinations. Graduates may additionally meet the academic requirements for Chartered Information Technology Professional (CITP) status, subject to appropriate professional experience after completing the programme.

Meet the needs of employers

This programme is designed to reflect the skills and knowledge demanded by employers across industry, government, and the digital economy. Throughout the programme, you will work with realistic, industry-relevant datasets and problem scenarios, both in supervised sessions and through independent study, developing practical experience in solving complex analytical challenges. 

We maintain strong links with industry partners, including organisations such as Rolls-Royce and local digital technology companies. These collaborations, together with research and consultancy projects, help ensure that the curriculum remains aligned with current professional practice and emerging industry needs.

By studying this course, you will:

• develop specialist knowledge in advanced data science, including data acquisition, management, analysis, visualisation, and responsible use of data 

• apply advanced statistical, analytical, and computational techniques to real-world problems 

• gain a critical understanding of how data science interacts with business, engineering, healthcare, and other scientific domains 

• build the ability to bridge theory and practice, translating analytical insights into practical solutions 

• learn to communicate complex findings clearly and effectively to both technical and non-technical audiences 

• develop as an independent and reflective practitioner, capable of working both autonomously and as part of multidisciplinary teams 

Please note that our modules are subject to change - we review the content of our courses regularly, making changes where necessary to improve your experience and graduate prospects.

You will develop practical and professional data science skills through workshops, laboratory sessions, and applied coursework. Many activities involve technical tasks, data analysis exercises, and small projects, while others focus on applying concepts, tools, and techniques to realistic case studies, practical scenarios, and organisational contexts. 

Practical skills are further strengthened through laboratory-based exercises, guided tutorials, and coursework assessments. A successful data science professional requires a broad combination of technical, analytical, and communication skills, so the programme uses a variety of learning approaches designed to support different learning styles and professional development. 

Teaching and learning methods may include:

• face-to-face lectures and tutorials, providing the core concepts and theoretical foundations 

• invited talks and seminars from industry partners  

• hands-on laboratory and software-based practical sessions 

• case studies based on real-world data and applications 

• problem-solving and enquiry-based learning activities 

• student presentations and group discussions 

• debates and collaborative exercises to develop critical thinking and communication skills

Teaching methods are adapted where appropriate to meet the needs of individual students, ensuring an inclusive and supportive learning environment.

How you will be assessed 

Throughout the programme, you will experience a range of assessment methods designed to evaluate both your theoretical understanding and your practical and professional skills. Assessments emphasise applied work and real-world problem solving, reflecting how data science is practised in industry. 

Assessment methods may include:

• coursework assignments, such as data analysis reports, programming tasks, and case studies 

• technical and design documentation, where you plan and justify analytical or software solutions 

• individual or group presentations to develop communication and professional skills 

• practical demonstrations of data processing, modelling, or analytical solutions 

• research-based projects that develop independent inquiry and critical thinking 

• a substantial independent dissertation or thesis, where you will investigate a data science problem in depth and apply appropriate techniques and methods

These assessment approaches are designed to help you develop the analytical, technical, and communication skills expected of modern data scientists, including the ability to present complex findings clearly to both technical and non-technical audiences.

Graduates from the programme will be equipped for careers in business intelligence and data analytics, which includes the analysis and extraction of information from Big Data sets relating to any type of industry or business. Graduates will also gain high level skills and knowledge pertaining to consultancy and entrepreneurship.

The MSc Advanced Data Science will provide you, on successful completion, a step up in your professional development and give you excellent employment potential. There is a growing demand for Advanced Data Science professionals and the programme provides a postgraduate qualification that directly meets the needs of today's working environments with regard to a variety of emerging and innovative technologies and challenges posed by the increasingly complex networked world of modern society.

Information Technology professionals who can identify the root causes of business issues and have the ability to model/analyse complex daily life scenarios as well as complex technical, biological, chemical, engineering, financial or economical systems and processes are much sought after.

As well as offering a route to further study at PhD level, successful completion of this programme will enable you to enter, or return to work, more effectively and communicate your knowledge and skills to a broad audience of people with diverse backgrounds in order to be able to operate in and lead multidisciplinary teams.

The course will enable you to prepare to meet the academic requirements of the British Computer Society (BCS), enabling you to achieve Chartered Information Technology Professional status after completion subsequent satisfactory industrial experience post programme.

Applicants for the MSc Advanced Data Science programme will normally hold a 2.2 or higher Bachelor’s degree in a Science, Technology, Engineering, Mathematics (STEM) or a closely related discipline with significant mathematical content at an appropriate level, or an equivalent international degree.

Applicants who do not meet these criteria may still be eligible if they can demonstrate relevant work experience in a management or supervisory position, supported by employers’ references, and can demonstrate effective communication and learning skills and the motivation to succeed during an interview.

If English is not your first language, you will also need an IELTS score of 6.0 or the equivalent.

Where required, interviews will be conducted by the Programme Leader and may be undertaken by telephone where access to campus may be prohibitive.

Please note fees normally increase in line with inflation and the University's strategic approach to fees, which is reviewed on an annual basis. The total fee you pay may therefore increase after one year of study.

* UK full-time fees paid within one academic year are rounded down to the nearest £50 if applicable

Additional costs and optional extras

About postgraduate awards

Please note at postgraduate level, you'll need to gain the following number of credits in total to obtain the respective awards. If you have any questions please contact us.

This means you will gain 180 credits in total to complete the full MA or MSc. If you are studying part time you will normally complete your studies over two or three years, depending on the course structure.

Funding your studies

Find out more about fees, postgraduate loans and support you may be entitled to.

Find out about funding your studiesFind out about funding your studies

Alumni discount for Derby graduates

We offer a discount on postgraduate course fees for all Derby alumni.

Find out about the Alumni discountFind out about the Alumni discount

Additional information about your studies

If you join in September, the duration of the course will be one year. If you enrol in January, the course duration will be 18 months.

Teaching hours

Like most universities, we operate extended teaching hours at the University of Derby, so contact time with your lecturers and tutors could be anytime between 9am and 9pm. Your timetable will usually be available on the website 24 hours after enrolment on to your course.