Data Science (Statistics)
Basic Information
- Course ID
5656ea05-4213-4700-8263-1406cae66942- Option ID
ebf29068-856b-48c1-9c6c-bdf39c2f80bb- Provider
- University of Leeds
- Type
- postgraduate
- Academic Year
- 2026
- Source
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- Created
- 2/22/2026, 4:48:02 AM
- Updated
- 3/27/2026, 10:08:58 AM
Other Options for this Course
No other options
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"summary": "Developed in collaboration with the School of Mathematics and the Leeds Institute for Data Analytics, our online Data Science (Statistics) masters degree offers you the opportunity to learn in-demand data skills such as data acquisition, data preparation, data wrangling, modelling and analysis, and how to deal with missing data.\n\nWhether you have an undergraduate degree in a quantitative subject with substantial elements of mathematics and statistics or you’re already working in a data-driven STEM field, you’ll be ready for business-critical senior roles in areas such as healthcare or environmental science.\n\nThe MSc Data Science (Statistics) offers a comprehensive curriculum that spans from foundational data science courses to specialised statistics courses. You'll also learn industry best practices and study widely used methods to understand and interpret data in a range of contexts. Because employers are looking for job candidates who can tell compelling stories with data, your projects in this programme will give you opportunities to combine different methods of presentation.\n\nUsing research from Leeds Institute of Data Analytics, and others, you’ll work on projects in innovative areas such as AI, health informatics, urban analytics, statistical and mathematical methods, and visualisation and immersive technologies. Experience in these areas will help you prepare for the future of data science.\n\nAs a graduate of this programme, you'll be able to:\n\n\n- Illustrate a comprehensive understanding of key statistical methods and their practical application.\n\n\n- Demonstrate thorough knowledge in various specialised topics within statistics such as Baysian modelling, Monte Carlo estimation and dimension reduction.\n\n\n- Select and apply tools and techniques for using statistical methods on context.\n\n\n- Acquire transferable skills and the ability to work independently through the completion of a practical data analysis project.\n\n\n- Build proficiency in key programming languages and techniques for data analysis.\n\n\n- Develop effective analysis strategies for traditional “simple random sample” and a “big data” (population) datasets differ.\n\n\n- Analyse large datasets (including ones with more variables than observations).\n\n\n- Describe issues of data ethics and governance, as well as evaluate the impact of these issues on data gathering and analysis.\n\n\nThis online degree is offered through the Coursera platform: https://www.coursera.org/degrees/msc-data-science-ul \n\nThe next cohort starts on 8 January 2024.",
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"scrapedLanguageRaw": "Proof of your English Language Proficiency\nProficiency in English language is essential to study at the University of Leeds. You will need either:\nAlternative English Language Qualification\nA degree taught in English from a recognised institution, lasting at least two years at the undergraduate level or one year at the Masters level, which can be evidenced by transcripts and/or certificates.\nFor more details, contact our Enrolment Advisors at onlineadmissions@leeds.ac.uk\nPriority Deadline: 11 June 2026\nSubmit your complete application, including all required documents, by 11 June 2026. You will then qualify for free access to six University of Leeds Data Science (Statistics) short courses, upon receipt of an offer:\nProgramming for Data Science\nData Storytelling and Presentation Skills\nHow to Plan Projects, Research and Reflect\nEthical decision-making in practice\nThis offer provides an opportunity to begin learning and prepares you for success in the MSc Data Science (Statistics) programme.\nEnglish language requirements\nIELTS 6.5 overall, with no less than 6.0 in any component. . For other English qualifications, read English language equivalent qualifications.",
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"scrapedEntryRequirements": "Entry requirements Full entry requirements ApplyingEntry requirementsRoute 1: Standard EntryTo meet the standard entry requirements, you need a 2:1 Bachelor of Science honours degree (3.0 GPA). Transcripts should show evidence of at least 5 undergraduate modules in a combination of mathematics and statistics. At least one module should be in Statistics, and all modules should be across at least 2 years of your previous study.Route 2: Performance Pathway To qualify for the performance pathway entry route, you need to meet one of the following criteria:a minimum of a third-class Bachelor of Science honours degree (2.2 GPA) or a minimum of a third-class Bachelor of Engineering degree (2.2 GPA), orat least 3 years of relevant professional experience. This experience should demonstrate competencies in:Working with large data setsVisualising and summarising data“Cleaning” dataData modellingStatistical analysisUsing statistical software such as R, SPSS, or PythonWe will send you an additional"
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