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00 - General Content
01 - Schema Data
02a - Course Title: Statistics with Data Science MSc
02b - Short Description: Develop advanced statistical and data science skills to uncover insights from complex data and solve real-world problems.
03 - Archive Button

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A

A0 - Info Blocks

A0 - Tags

Postgraduate Taught

A1 - Course Code

P-G4P1

A2 - Start Date

27 September 2027

A3 - Study Location

University of Warwick

A4 - Qualification

Master of Science (MSc)

A5 - Department

Department of Statistics

A6 - Duration

1 year full-time

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C

C0 - Course Overview

C1 - Course Overview - Introduction

Master statistics in the age of data.

Data is transforming every sector of the modern economy. From healthcare to marketing, organisations need professionals who can extract meaningful insights from complex information. Through rigorous statistical training, our MSc equips you with the analytical, computational and problem-solving skills needed to thrive in a data-driven world. Graduates are well prepared for PhD study, or careers in sectors such as marketing, insurance, banking and pharmaceuticals.

C2 - Course Overview - Image

Group of people gathered around a chalkboard as one person writes equations.

C3 - Course Overview - Testimonial

OVERVIEWTESTIMONIAL

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D

D0 - Modules

D1 - Introduction

Develop expertise in statistics, data science and computational methods.

Statistical foundations: build a strong understanding of modern statistical theory and practice
Data science theory: explore the principles underpinning data science
Specialist techniques: study topics such as statistical learning and big data, Bayesian forecasting and Monte Carlo methods
Computational skills: enhance your expertise in areas such as high-performance computing, natural language processing and image & video analysis

Note that information found by following the links to the module catalogue is subject to change for future years of study, as we evolve our courses in response to the latest developments in academia and industry.

D2 - Modules - General

Further to the core modules students choose 5 optional modules.

For the MSc in Statistics with Data Science your optional modules are geared towards covering themes in Bayesian statistics, machine learning, statistical learning, topics in data science, Monte Carlo methods.

Subject to availability, you will also have access to a varying selection of modules from the Computer Science Department.

Availability of optional modules can change from year to year but may include the following examples:

You may also choose up to three modules from a broad range of statistics and probability modules available on the MSc in Statistics.

D2 - Modules - QUAL-2

D2 - Modules - QUAL-3

D2 - Modules - QUAL-4

D2 - Modules - QUAL-5

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E

E0 - Teaching and Learning

E1 - Teaching and learning Intro

Combine statistical rigour with practical data science expertise.

Analytical thinking: learn to interpret complex data and draw robust conclusions
Technical expertise: develop advanced quantitative and computational skills
Real-world applications: tackle data-driven challenges across a range of industries

E2 - Class sizes

The class sizes for this course vary between 30 and 70 students.

E3 - Contact hours

Contact hours for this course will vary between 12 and 16 hours each week.

E4 - Assessment

Assessment is initially made for each module separately: some modules have an element of continuous assessment through coursework, but but the majority of modules are assessed through written examinations in January, April and summer exam period.

Your performance in the core and optional modules combined is then examined by an examinations board consisting of academic staff plus an External Examiner appointed from another university. Dissertations are examined in the Department and then by the External Examiner.

The MSc degree is awarded subject to satisfactory standard in the dissertation and the taught modules. Students who do outstandingly well in both taught modules and the dissertation may be awarded the MSc with Distinction or Merit.

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F

F0 - Entry Requirements

F1 - Minimum requirements

2:1 undergraduate degree (or equivalent) in Statistics, Mathematics or a science with sufficiently high mathematical content.

F4 - English Language Requirement

Band A
IELTS overall score of 6.5, minimum component scores not below 6.0

F5 - Additional requirements

Students are expected to have pre-existing standard undergraduate knowledge in statistics and probability covering probability, random variables, expectations and important inequalities (see, for example, Part 1 in “All of Statistics: A Concise Course in Statistical Inference” by Larry Wasserman, Springer Texts in Statistics).

Students planning to take modules in probability and/or finance will be exposed to measure theory and must have a solid foundation in real analysis.

If you would like to view reading lists for current or previous cohorts of students, most departments have reading lists available through Warwick Library on the Talis Aspire platformLink opens in a new window.

You can search for reading lists by module title, code or convenor. Please see the modules tab of this page or the module catalogue.

Please note that some reading lists may have restricted access or be unavailable at certain times of year due to not yet being published. If you cannot access the reading list for a particular module, please check again later or contact the module’s host department.

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