Data Science BSc

3 Years On Campus Bachelors Program

University of Warwick

Program Overview

The BSc in Data Science at Warwick is an exciting three-year programme designed for curious, tech-driven problem solvers. It blends mathematics, statistics, and computing into a powerful toolkit, preparing you to turn raw data into real insights. If you’re someone who loves uncovering patterns, building smart algorithms, and using technology to solve big challenges, this degree gives you the perfect platform.


Curriculum Structure

Year 1
Your journey starts with a strong foundation in the essentials. You’ll explore programming, algorithms, calculus, vectors, and probability, while also learning how to structure information and model data statistically. Expect plenty of hands-on experience—whether it’s writing code in Java, building linear programming models, or running statistical analyses in R. By the end of your first year, you’ll already be thinking like a data scientist, with sharp problem-solving and algorithmic skills.

Year 2
In your second year, you’ll deepen your knowledge and expand your technical toolkit. Core topics include databases, algorithms, and software engineering, alongside more advanced statistics. You’ll also get the freedom to start shaping your own pathway with optional modules—whether your interests lean towards artificial intelligence, decision-making, or data visualisation. This flexibility means you can begin specialising early in areas that excite you most.

Year 3
Your final year is all about independence and choice. Around three-quarters of your modules will be optional, giving you the chance to dive deep into advanced topics such as Machine Learning and Bayesian Forecasting. A highlight is the Data Science Project—your chance to bring everything you’ve learned together in a real, full-scale analysis project. You’ll design it, carry it out, and present it, just like you would in industry or research.


Focus Areas

The degree combines the best of mathematical and statistical modelling, algorithm design, software engineering, machine learning, data mining, and data visualisation—giving you a truly interdisciplinary skillset.


Learning Outcomes

By the end of the course, you’ll be able to:

  • Think critically and analytically about data-driven problems.

  • Code with confidence and clarity.

  • Apply statistical reasoning to real-world challenges.

  • Design and implement efficient algorithms.

  • Deliver independent, professional-level data projects from start to finish.


Professional Alignment

Although there isn’t a specific external accreditation, the programme is taught by Warwick’s world-leading Departments of Statistics, Computer Science, and Mathematics. This means you’ll benefit from cutting-edge teaching, strong research connections, and content designed with industry in mind.


Reputation & Employability

A Warwick Data Science degree sets you up for careers where analytical and computational skills are in high demand. From finance, telecoms, and pharmaceuticals, to manufacturing, research, and beyond—graduates are highly sought after. Employers recognise the Warwick blend of technical depth, practical experience, and flexible specialisation as a mark of real quality.

Experiential Learning (Research, Projects, Internships etc.)

From your very first day, you’ll be working with real-world data challenges. In the early years, the focus is on building a solid foundation in mathematics, statistics, and computing. By your final year, you’ll take on a substantial Data Science project—an opportunity to apply everything you’ve learned while working closely with faculty across Statistics, Computer Science, and Mathematics. On top of this, all final-year BSc students complete a six-week, full-time laboratory or data-analysis project, choosing from hundreds of different options, each supported by dedicated academic staff.

Transitioning into the specifics of what this means for you:

Data Science Project and Final-Year Research:
You’ll undertake a major, faculty-supported project—whether lab-based or data-focused—where you design, carry out, and present research in a way that mirrors real-world professional or academic work.

Lab Access and Software Experience:
You’ll get hands-on with powerful tools like R, using it for exploratory data analysis, simulations, and statistical modelling, so you graduate confident in applying these methods to genuine datasets.

Advanced Computational Modules:
As you progress, you’ll have the chance to explore specialist topics such as Hadoop, Spark, deep learning, and streaming algorithms—giving you practical insight into the kinds of systems and computational approaches used in industry today.

Collaborative, Cross-Department Learning:
The programme is taught across several departments—Statistics, Computer Science, Mathematics, and even Warwick Business School. This means you benefit from a blend of expertise and perspectives, preparing you for the interdisciplinary nature of real data science work.

Placement and Exchange Opportunities:
You’ll also have the option to take a year out for an industry placement or study abroad. For example, students have the chance to join exchange programmes with universities such as HKUST. Both opportunities are supported by Warwick’s Industrial Liaison Team and academic staff, ensuring you’re well guided wherever you go.

Progression & Future Opportunities

Graduates of Warwick’s BSc Data Science program don’t just crunch numbers—they turn complex data into meaningful insights that help drive real-world decisions. Many move into exciting fields such as technology, finance, research, and consultancy. Because the course builds a strong foundation in statistics, computing, and mathematics, you’ll be ready to step into fast-growing, high-impact careers from the very start.

University services that help you land a job

From the moment you join Warwick, you’ll have access to tailored career support. The dedicated Careers Service helps you explore internships, build work experience, and sharpen your career plans. You can also make use of the Student Opportunity Hub, which provides one-to-one guidance and runs events that connect students directly with employers.

Employment stats and salary figures

Warwick’s graduates see strong career outcomes:

  • Around 90% of Data Science graduates are in work or further study within 15 months of finishing the degree.

  • Typical earnings at that stage are around £37,500, with most falling between £33,500 and £44,500.

  • Longer term, salaries grow significantly—after five years, graduates often earn an average of £59,000, with many in the £46,500–£81,000 range.

University–industry partnerships

As a Warwick student, you benefit from being part of a wider innovation community. Through groups like WMG (Warwick Manufacturing Group)—a leading centre for manufacturing research and industry collaboration—you’ll see how academic learning translates into practical, industry-driven solutions. These links open up valuable opportunities for students to get involved in real projects.

Long-term accreditation value

The BSc Data Science is accredited by the Royal Statistical Society (RSS). This means you can apply for Graduate Statistician status, a respected professional recognition that signals your expertise to employers and gives you an edge as you progress in your career.

Graduation outcomes

When it comes to career paths, Warwick graduates go into a wide range of professional roles. About half move into IT-related positions, 10% head into finance, another 10% into science and engineering associate roles, and around 10% into business and public service. Across all of these fields, they’re applying the skills gained from the degree to solve complex problems and shape the future.

Program Key Stats

£33,520
£9,535
£ 29
Sept Intake : 14th Jan


No
Yes

Eligibility Criteria

A*A*A*
N/A
39
92

N/A
N/A
6.0
87

Additional Information & Requirements

Career Options

  • Data analyst
  • data scientist
  • machine learning engineer
  • business intelligence analyst
  • quantitative analyst
  • software engineer
  • risk analyst
  • operations analyst
  • data consultant
  • financial analyst
  • research scientist
  • big data engineer
  • statistical modeller
  • AI specialist
  • systems analyst
  • data visualisation specialist

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