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MSc Data Science and Machine Learning
Why choose Herts?
- Industry Accreditation: Accredited by the British Computer Society (BCS) enabling graduates to register at The Chartered Institute for IT as a chartered IT professional.
- Work Placement Opportunities: You have a one-year placement option enabling you to gain real industry experience.
- Employment Prospects: Graduates in our department are now data scientists, data engineers, and data analytics consultants working for organisations including BT, IBM and Microsoft. 96% of postgraduates are in work or study (Graduate Outcomes, 2025)1
1from 2022/23 graduates, in employment or further study 15 months after graduation.
Professional Accreditations
Accredited by BCS, The Chartered Institute for IT for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.
About the course
This course is part of our master's programme in computer science.
The MSc in Data Science and Machine Learning draws on our internationally recognised research in data science and machine learning. It is informed by the expertise of our academic staff and reflects current research and practice in the field. The course develops your understanding of how to obtain data from a range of sources, alongside key methods for data pre-processing, cleaning, analytics, and modelling.
The programme offers three award routes that you can choose to study:
- MSc Data Science and Machine Learning
- MSc Data Science and Machine Learning with Extended Professional Practice
- MSc Data Science and Machine Learning with Advanced Research
Why choose this course?
- One of a range of advanced courses within our postgraduate master's programme in computer science, this particular course provides you with a specialism in data science and machine learning.
- You will be taught by a highly regarded and long-established computer science department, with 90% of its research ranked as world-leading (Research Excellence Framework, 2021).
- Gain hands-on experience across the full lifecycle of data science and machine learning applications. You will study image processing, time series analysis, and natural language processing, with applications in finance, healthcare, marketing, and both real-time and historical data contexts.
- Develop practical teamwork experience by applying skills in cloud computing, big data, machine learning, and data visualisation using industry-standard tools.
- Build expertise using industry-relevant tools and practices, including system administration, cloud computing, software development, database administration, machine learning, and data visualisation. You will also learn to critically review and evaluate emerging technologies and research, enabling you to adapt to new challenges in data engineering.
- Acquire fundamental mathematical knowledge essential for data science, including linear algebra, set theory, advanced calculus, probability, and statistics. You will learn to apply these foundations as computational techniques to solve real-world problems.
- Explore research-informed topics in neural network theory and design, gaining insight into the technologies underpinning modern tools such as large language models. Teaching draws on the School’s research strengths in biocomputation, evolutionary algorithms, and neural networks.
What will I study?
The course is delivered through a combination of core modules that develop both theoretical understanding and practical skills in data science and machine learning. You will cover key areas including data engineering and teamwork, real-world data science applications, mathematical and programming foundations, neural networks and machine learning, and responsible technology practice. In the final project, you apply your knowledge and skills to an independent, substantial piece of work in data science and machine learning.
Technologies evolve each year to reflect advances in data science. You can expect to use tools such as Jupyter Notebook/Lab with Python libraries for visualisation and machine learning, PySpark, SQL, Git, MATLAB, R and more.
Some modules include hands-on experience with Linux-based environments for developing and deploying data analysis workflows.
Subject to availability, the School regularly offers co-curricular data science activities. The Data Science Project Club is a well-established example, where students enhance their technical, poster design, and presentation skills, with prizes awarded to the strongest teams.
You will also benefit from industry engagement through workshops and hackathons delivered by external speakers, including events such as AI agent workshops and data science industry hackathons.
Teaching is delivered through lectures, small group seminars, and practical laboratory sessions. You will use modern, industry-standard software throughout, supported by specialist facilities for networking and multimedia, as well as a dedicated masters project laboratory.
In addition to scheduled classes, you will be expected to undertake significant independent study. Our Learning Resource Centres (LRCs) are open 24/7 and provide a wide range of facilities, including study spaces, computer access, specialist software, laptop loans, printing, Wi-Fi, and bookable group study rooms. Online resources and study support services are also available.
Where will I study?
Learn in our new School of Physics, Engineering and Computer Science building (SPECS), where you’ll benefit from a range of experiential learning zones.
The computer science laboratories are home to telecommunications, robotics and UX empathy labs, with a variety of research spaces that range from dark rooms to clean rooms, and sample prep labs to calibration and assembly labs.
You will also benefit from our Academic Support Hub, which is aimed at helping you build your employability and academic skills. Plus, have access to industry mentors who will provide you with pastoral support, vocational guidance, and career progression opportunities.
Spectra also provides space to collaborate, with plenty of workshops, social and meeting spaces available. Even better, the building has been designed with the University’s net zero carbon target in mind, and forms part of our plan to replace or upgrade older sites that are energy inefficient.
Further course information
| Programme specifications | |
|---|---|
| MSc Data Science and Machine Learning - Full Time, Sem B | Download |
| MSc Data Science and Machine Learning - Full Time, Sem A | Download |
| Additional information | |
|---|---|
Sandwich placement or study abroad year |
n/a |
Applications open to international and EU students |
Yes |