Program Overview

Data Science MSc

Overview

Big data is playing an increasingly important role in our society. The need for expert and ethically-informed data analysis is in high demand across many industries. This course gives you the professional and problem-solving skills for a range of high-level careers.

This interdisciplinary masters will be taught by the Schools of Computer Science and Mathematical Sciences. Our academics conduct their own international-quality research. They use this to teach you the latest techniques and technologies in this field.

Develop your knowledge in key topics such as statistical modelling, machine learning and advanced algorithms. We offer a range of flexible optional modules. This allows you to study a topic that interests you.

You will undertake an individual research project in an area of your choice. This can be with industry partners or with one of our expert research groups. Past projects have included:

• Development of location-based service for education
• UK precipitation forecasting
• The effect of virtual audiences on music performance anxiety

Why Choose This Course?

• Ranked 6th in the UK for universities targeted by the largest number of top employers in the High Fliers Report The Graduate Market
• 96.4% of postgraduates from the School of Computer Science secured work or further study within six months of graduation (HESA Graduate Outcomes 2020, using methodology set by The Guardian)
• Conversion option: No computer programming experience is needed. Your modules will depend on your background in computer science.
• Joint 1st in the UK for research environment (Research Excellence Framework 2021)
• 98% of our research is classed as ‘world-leading’ (4) or ‘internationally excellent’ (3) (Research Excellence Framework 2021)

Course Content

You will study a total of 180 credits, split across 120 credits of compulsory and optional modules plus a 60-credit individual project.

No computer programming experience is needed. We offer two pathways for this course depending on your background. You will be guided to choose an appropriate set of modules based on your prior computer science and mathematics experience.

Modules

• Research Project (60 credits)
• Students with a degree in Computer Science or equivalent are required to obtain between 40 and 80 credits from the following list of Computer Science modules:
  • Machine Learning (20 credits)
  • Project in Advanced Algorithms and Data Structures (10 or 20 credits)
  • Computer Vision (20 credits)
  • Simulation and Optimisation for Decision Support (20 credits)
  • Data Science with Machine Learning (20 credits)
  • Linear and Discrete Optimisation (20 credits)
  • Handling Uncertainty with Fuzzy Sets and Fuzzy Systems (20 credits)
  • Big Data Learning and Technologies (20 credits)
  • Designing Intelligent Agents (20 credits)
• Students without a background in Computer Science must start with:
  • Programming (20 credits)
• And are then required to obtain between 20 and 60 credits from the remaining list of Computer Science modules:
  • Data Science with Machine Learning (20 credits)
  • Computer Vision (20 credits)
  • Machine Learning (20 credits)
  • Simulation and Optimisation for Decision Support (20 credits)
  • Databases, Interfaces and Software Design Principles (20 credits)
  • Handling Uncertainty with Fuzzy Sets and Fuzzy Systems (20 credits)
  • Big Data Learning and Technologies (20 credits)
  • Designing Intelligent Agents (20 credits)
• Mathematical Sciences modules:
  • Students without a background in Mathematical Sciences must start with:
    • Applied Statistics and Probability (20 credits)
  • Students without a degree in Mathematical Sciences or equivalent are required to obtain 20 to 60 credits from the following list of Mathematical Science modules:
    • Statistical Modelling (20 credits)
    • Time Series and Forecasting (20 credits)
    • Applied Multivariate Statistics (20 credits)
  • Students with a degree in Mathematical Sciences or equivalent are required to obtain 40 to 80 credits from the following list of Mathematical Science modules:
    • Applied Multivariate Statistics (20 credits)
    • Statistical Modelling (20 credits)
    • Computational Statistics (20 credits)
    • Time Series and Forecasting (20 credits)
    • Statistical Machine Learning (20 credits)
    • Classical and Bayesian Inference (20 credits)

Learning and Assessment

• How you will learn:
  • Lectures
  • Tutorials
  • Seminars
  • Computer labs
  • Practical classes
  • Project work
  • Supervision
• How you will be assessed:
  • Coursework
  • Written exam
  • Project work
• Modules are assessed using an appropriate mixture of coursework and exams which are combined to calculate your final mark for each module.
• The final degree classification will be the average of all credits, e.g. an average of 120 taught credits and 60 credits on your project.
• To pass a module you’ll need at least 50%.

Entry Requirements

• All candidates are considered on an individual basis and we accept a broad range of qualifications.
• The entrance requirements below apply to 2026 entry.
• Undergraduate degree: 2:1 (or international equivalent) with an affinity for programming and/or advanced statistics evidenced through prior study or practical experience detailed in the application.
• Graduates from other fields, with strong mathematics and/or computer science background will be considered with 60% average mark.
• International and EU equivalents: We accept a wide range of qualifications from all over the world.
• English language requirements: IELTS 6.5 with at least 6.0 in each element.

Fees

• Qualification: MSc
• Home / UK: To be confirmed
• International: To be confirmed
• Please note that course fees for 2026 entry have not yet been confirmed.

Careers

• We offer individual careers support for all postgraduate students.
• Expert staff can help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.
• Each year 1,100 employers advertise graduate jobs and internships through our online vacancy service.
• We host regular careers fairs, including specialist fairs for different sectors.
• International students who complete an eligible degree programme in the UK on a student visa can apply to stay and work in the UK after their course under the Graduate immigration route.
• Eligible courses at the University of Nottingham include bachelors, masters and research degrees, and PGCE courses.

Graduate Destinations

• This course prepares you for careers in advanced software development, particularly where reliability and efficiency are vital requirements.
• Graduates are likely to assume leading roles in major software-development projects in one of the areas of specialisation.
• This course also provides an excellent foundation for further study and you may decide to progress to a PhD in order to continue your research.

Career Progression

• 100% of postgraduate taught students from the School of Computer Science secured graduate level employment or further graduate study within 15 months of graduation.
• The average annual salary for these graduates was £30,100 (HESA Graduate Outcomes 2019/20 data published in 2022).