Taught course
Data Science and Machine Learning with Advanced Project
Entry requirements
For admission to MSc Data Science and Machine Learning with Advanced Project, the requirement is a good honours degree (or equivalent) in a STEM subject, or a non-STEM subject with relevant experience. The choice of award title students may be accepted on to will be determined by the award applied for and the prior learning of the student as demonstrated by the transcript for existing qualifications held by the applicant.
Applicants whose first language is not English must demonstrate sufficient competence in the language to benefit from this postgraduate degree. This is demonstrated by recognised awards equivalent to an overall IELTS score of 6.0. Candidates who do not satisfy these requirements will be considered on a case-by-case basis.
The MSc Data Science and Machine Learning with Advanced Project degree is subject to the University's Principles, Policies and Regulations for the Admission of Students to Undergraduate and Taught Postgraduate Programmes (in UPR SA03), along with associated procedures. These will take account of University policy and guidelines for assessing accredited prior certificated learning (APCL) and accredited prior experiential learning (APEL).
Months of entry
January, September
Course content
The MSc Data Science and Machine Learning with Advanced Project draws on our internationally recognised research in data science and machine learning and is informed by current industry practice.
You will develop advanced knowledge of data science techniques, including data pre-processing, cleaning, analytics, and modelling.
The postgraduate degree combines theoretical understanding with hands-on technical training, helping you develop the skills you need to work with complex datasets and apply data-driven solutions to the real-world challenges. You’ll develop the ability to write clean and efficient code in industry-recognised languages including Python and R, alongside developing techniques in data handling, manipulation, mining and visualisation techniques.
Qualification, course duration and attendance options
- MSc
- full time24 months
- Campus-based learningis available for this qualification
Course contact details
- Name
- Ask Herts
- ask@herts.ac.uk