The details
Location: Online Mode of study: Part-time Qualification: BSc Indicative duration: 4 years
Start date: Awarding body: University of Essex Delivered by: Kaplan Open Learning For queries: Call +44 (0) 1206 489 358

There’s a growing demand for data science and analytics experts, as organisations increasingly process sensitive customer information. Learn how to protect business reputation, remain GDPR compliant and drive smart decision-making with our BSc (Hons) Data Science. 

This undergraduate degree is ideal if you’re looking to enter the world of data science or already work within the industry but wish to gain professional qualifications. From data visualisation to machine learning, you’ll explore key areas of data science – allowing you to develop a holistic understanding of their application in achieving business objectives. 

You’ll delve into a range of interesting topics, including:  

  • the role of maths and statistics in data processing 
  • key aspects of SQL  
  • object-oriented programming techniques  
  • the role of AI in the data cycle 

And upon completion, you’ll have developed the in-depth knowledge, skills and competencies to succeed in the field. You could even continue your studies with our postgraduate MSc Data Science. 

Please note, this course is currently undergoing validation and the structure, including module titles, may be subject to change. 

Why we’re great

  • Explore a range of programming, language processing and data mining techniques.  
  • Develop your research and analytical skills.  
  • Gain the support and guidance of experienced tutors. 
  • Study with a top 25 UK university (Guardian University Guide 2025).  
  • We were rated Gold in the Times Higher Education (THE) Online Learning Rankings 2024. 

The BSc (Hons) Data Science is made up of the following modules and, upon completion, is equal to a total of 360 credits. 

Develop the fundamental skills required to engage in research activities, project management and professional conduct. This module incorporates relevant themes – including how to adopt sustainable development goals, minimise impact and promote social responsibility. You’ll also begin building your entrepreneurial skills and understanding of research methodologies through theoretical discussion, practical exercises and real-world case studies.

How do maths and statistics affect decision making in sustainable practices? Find out in this informative module. From summary statistics, hypothesis testing and linear algebra, to permutations, probability and parametric and non-parametric tests, you’ll cover a range of mathematical and statistical applications. And by the end, you’ll have a strong understanding of how they’re integral to the role of a computer scientist. 

Gain a comprehensive introduction to programming. By writing, testing and debugging through Python, you’ll develop a strong understand of coding and the impact on software development. There’s also a strong emphasis on inclusive and sustainable software, as you explore the role of software in society and beyond.  

Ready to discover the fundamental principles of object-oriented programming (OOP) and their application in software development? From inheritance and polymorphism to encapsulation and abstraction, this module introduces key OOP concepts and techniques, giving you a solid foundation for a future career in computing. There’s also a strong focus on sustainability, as you consider resource-conscious software solutions to reduce energy consumption and waste. 

Discover how to work with data in this exciting module. You’ll analyse the key concepts of SQL such as relations, keys and normalisation through the design and implementation of relational databases, ensuring you have a solid understanding of database design principles. 

Build the skills you need to succeed in your future computing career. Following a team-based projects framework, you’ll choose a team project that aligns with specific attributes that fit with your chosen topic. That way, you’ll develop a strong understanding of various professional competencies and ethical standards in project development. 

Did you know data science plays a key role in medicine, climate science and business analytics? Discover the fundamental concepts of this rapidly growing field, as you explore key tools and techniques – as well as ways to analyse both textual and numerical data. By the end, you’ll have developed strong analytical skills and be ready to explore various application domains where data science is relevant. 

Gain a thorough introduction to cybersecurity with this informative module. Through hands-on exercises and real-world case studies, you’ll explore cryptography, user authentication, operating system security, malware forensics and more – ensuring you’re well prepared for a career in this sector.  

Artificial intelligence is a rapidly growing area – and this module offers an introduction to all facets of AI. You’ll explore the methodologies and techniques of search algorithms, knowledge representation and learning mechanisms – as well as the role of AI in computer games and robotics. And at the end, you’ll gain an in-depth understanding of systems bult upon interacting intelligent acts. 

Discover how to design energy-efficient information retrieval (IR) systems in this inspiring module. You’ll learn all about the theoretical foundations of IR systems – such as text processing, indexing and querying – while considering how to minimise the carbon footprint of digital information processing during design and development. That way, you’ll have a strong understanding of the role IR systems in building environmentally responsible systems that drive social and economic value. 

How do computer programs perform everyday language tasks? Find out in this exciting module. You’ll be introduced to the three fundamental concepts of natural language processing (NLP): understanding the structure and grammar of language; considering language processing tasks that are simple for humans but challenging for computers; and using intelligent computing techniques to solve these challenges. 

Learn how to keep computer networks safe from cyber-attacks in this informative module. You’ll begin by exploring the principles, techniques and tools used to secure computer networks before moving on to network analysis, threat assessment and cryptographic approaches, and how these apply to real-life scenarios. 

Teaching methods 

Studying online gives you the freedom to study when and where it suits you – at home, during your lunch hour or anywhere else you have internet access.  

Our courses are delivered through a virtual learning environment (VLE) instead of a traditional campus. This means you’ll have access to your study materials 24/7, including:  

  • multimedia lecturecasts made up of written content, short videos, animation, audio recordings, infographics, short tests and mini-assignments 
  • discussion forums for you to chat about the course content with fellow students 
  • live seminars and Q&A sessions with your tutors 
  • a comprehensive eLibrary of textbooks and academic journals  
  • support from academic staff and your dedicated Student Support team 

 

Assessments 

You’ll be assessed through a series of assignments. This can be by engaging in discussion forums throughout your modules, completing reflective journal entries, delivering live presentations or by submitting longer written pieces. 

We’re committed to providing frequent and transparent feedback in the following ways: 

  • our assessment criteria are designed to be simple and transparent 
  • you’ll always be aware of your current provisional grade, right from the start of the programme 
  • you’ll be able to view your marks clearly in your gradebook whenever you log into the learning platform 
  • there’s a 7-day turnaround for marking and feedback of assessed work 
  • you’ll have regular contact with your Student Support team, with whom you can discuss any concerns as soon as they arise 

 

Online learning experience 

Your learning experience will be fully supported by high-quality learning materials and resources, delivered via our state-of-the-art virtual learning environment (VLE).  

On average, your learning experience will include the following: 

  • directed learning (40%) this includes participating in tutor-led discussions and seminars, completing interactive exercises on the VLE, and watching videos and lecturecasts. You’ll also be able to book appointments with your module tutor during their office hours, which can be found on the VLE 
  • self-directed learning (30%) – including undertaking wider reading and research in your area of study to develop your understanding of the subject area 
  • assessment (30%) time spent preparing and completing assignments and activities that contribute towards your overall assessment

Typically, you’ll need to dedicate a minimum 15-20 hours of study per module, per week. 

 

Study duration 

Our BSc (Hons) Data Science has an indicative study duration of 4 years, which is a guide to how long your course will take to complete. The actual duration may be longer or shorter depending on your speed of study, study options chosen and module availability.  

It’s possible to complete your studies faster than the indicative course duration by doubling up on modules at certain times; however, minimum study durations do apply.  

Our academic year is organised into modules, typically with a one or two-week break between modules and a structured three-week break for the Christmas period. Students will receive a course timetable during the application process.  

All our courses have regular start dates throughout the year.  

On successful completion of your degree, you’ll be invited to attend a graduation ceremony at the University of Essex’s Colchester campus. 

 

Academic staff 

A quality teaching experience is at the heart of everything we do.  

The dedicated tutors who teach our course modules are subject matter experts, experienced academics and leading industry thought leaders. They play a vital role in ensuring the latest theories and areas of study are covered in our courses, and are proud to provide a high level of academic support. 

You can find more information on our key academic staff and their experience here. 

 

Quality and assurance  

We’re proud to provide a first-class education to students anywhere in the world and adhere to the strictest quality standards 

The University of Essex Online is a recognised member of the Quality Assurance Agency for Higher Education (QAA) and registered with the Office for Students (OfS) 

All our degrees are delivered by Kaplan Open Learning, a world-leading education provider with over 15 years’ experience. 

An undergraduate degree in data science opens doors to many exciting careers within the industry. On completion, you’ll be ready to take on roles such as Data Scientist, Engineer, Analyst or Administrator; Site Reliability Engineer; Machine Learning Engineer; or Business Intelligence Analyst.  

You can also expand your studies with our eight-month PG Cert Data Science,16-month PG Dip Data Science or our full two-year MSc Data Science. 

 

Gaining an undergraduate qualification with the University of Essex Online also puts you in good stead for your career prospects. Results from our 2021 student survey showed: 

  • 92% of students said their course helped develop their research skills 
  • 89% of students say their studies fit with their future plans 
  • Almost 60% said their studies had a positive effect on their career 
  • 25% of students saw their salaries increase by up to 10% 

We know many people from non-traditional backgrounds would succeed on our courses! That’s why we offer two different entry routes, taking into account your prior work experience and relevant qualifications. You’ll also need to meet our English language requirements. 

Additionally, you’ll need to pass your first assignment set within your two-week induction period of the course in order to continue with your studies. 

 

Academic entry route

In order to satisfy the academic entry route requirements for our BSc (Hons) Data Science, you must have the following qualifications as a minimum: 

  • three A-levels or equivalent 

Work experience entry route

To satisfy the work experience entry route requirements for our BSc (Hons) Data Science, you must meet the following criteria as a minimum:  

  • GCSE Maths and English at grade C or above, or equivalent  
  • at least three years’ experience within the fields of IT, data science, computer science or business 

English language requirements

As our courses are delivered in English, a high proficiency is required in this language. If English isn’t your first language, your English ability should be equivalent to an IELTS (Academic) score of 6.0. Don’t worry if you don’t hold an IELTS or equivalent qualification – we offer a free online English test to assess your proficiency.  

You don’t need to prove your English ability if you are a national of, or have completed a qualification equivalent to a UK degree in, any of these countries. 

Full tuition fee:

£18,500 UK / £20,396 International (2024-25)  Δ

  • Designated for undergraduate student loans in England. 
  • Simple monthly payment plan available, enabling you to spread the cost over the duration of your studies. 
  • Full payment discount of 5% if you pay upfront. 
  • Partial scholarship available for international students residing in specific regions outside of the UK. 
  • Alumni discount of 10% of the tuition fee available if you’re a previous graduate with the University of Essex or University of Essex Online. 

Please note that a maximum of two discounts or scholarships can be applied. Find out more information about our discounts and scholarships here. 

Our course fees are fully inclusive – all teaching materials and required reading are included, and there are no hidden charges for assessments or resits.  

We want to give everyone the opportunity to experience a University of Essex Online course. We think you’ll love it, but if within the first 21 days you decide it’s not for you, you’ll receive a full refund. 

Δ All tuition fees shown are net of any applicable sales tax payable by you in your country of residence. Where we are required to add sales tax at the local statutory rate, this will be added to the tuition fees shown and confirmed during the payment process. 

Subject specialists, industry authorities and experienced academics: the tutors who teach modules on our BSc (Hons) Data Science are true experts in the field. 

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