BSc (Hons) Data Science
- Study Mode: Full Time
- Location: High Wycombe
- Duration: Three or Four Years
- Start Date: September 2024
Do you want to learn how to work with data and use it to make decisions? Looking for a degree with opportunities to work on real-life scenarios, business challenges and career-relevant problems?
BSc (Hons) Data Science teaches you the skills and knowledge to collect, store, analyse, and present data for different purposes and industries. It gives you the opportunity to learn from knowledgeable academics and industry experts.
* Please note this course is Subject to Validation.
Why study this subject?
With the modern world increasingly reliant on data-driven decision-making a degree in data science open doors to diverse career opportunities. BSc (Hons) Data Science provides you with in-depth knowledge of statistics, programming languages, and data handling. Equipping you with skills that are in high demand makes you well-positioned to enter the competitive job market.
Data Science is at the forefront of current technological advancements, offering a dynamic and intellectually stimulating career, where you can contribute your skills and make an impact. With great emphasis on developing your employability skills, Data Science provides you with the competence and confidence to pursue and succeed in these roles
Why study at Buckinghamshire New University?
At BNU, we always provide our students with opportunities to work on real-life scenarios, business challenges and work-relevant problems whenever we can which is why your experience as a student with us will be so unique.
We provide you with the latest, industry-standard software throughout the course, making sure all of your work is industry-relevant and preparing you for your future career.
What facilities can I use?
Our computing facilities are regularly upgraded so that you have access to the right hardware, software and technology, to succeed in your studies and to prepare you for employment.
What will I study?
The BSc (Hons) Data Science course teaches you how to work with data in a variety of different ways. You will learn how to collect, store, analyse, and present data for different purposes and industries. You will also learn how to use different tools and software to handle data.
This degree will help you acquire a range of transferable skills that are essential for academic and professional success, such as curiosity, critical thinking, adaptability, and research skills. You will also learn how to solve problems and find insights from data. You will learn elements of data visualisation, storytelling and its ethical use, as well as data automation with AI. This will help you understand the role that data-based computing can have in a range of business and industry contexts.
The course gives a balance of theory and practice, with opportunities to apply your knowledge to real or simulated projects and scenarios. You will focus on technical data analysis applications and services for industries that require expertise in data-focused computing sectors, using database development technologies.
How will I be taught and assessed?
BSc (Hons) Data Science uses a range of methods and technology to teach you in and out of class. You will participate in lectures, tutorials, seminars, and practical sessions. You will also learn from guest speakers, real projects, and visits to different places. You will become more independent and self-directed as you progress through the course. You will also have access to the BNU’s Virtual Learning Environment a digitally based platform that offers many features and resources to support and enhance your learning experience.
You will be assessed in different ways to prepare you for your future career. You will do different types of coursework (such as writing, doing, presenting, and working with others) and some tests or exams. You will also do a Project in your final year, where you will research a significant problem that is relevant to some current business challenge or your own career aspirations.
What are the course entry requirements?
A typical offer will require a UCAS tariff score of: 88 - 112 (Full-time) or 32 - 56 (Foundation Year)
UCAS points can be obtained through qualifications such as A levels, T levels, BTEC or an Access to Higher Education course in a relevant subject. Please list all your qualifications on the application form as you will be asked to provide copies when we receive your application.
A minimum of two full A-levels (or equivalent) is required. Every application is considered on an individual basis.
For further details of our international English entry requirements, please visit our international pages.
Applicants who do not meet the minimum requirements for the three-year undergraduate programme, or those who do not feel fully prepared for a degree course, can apply for a four-year programme including a Foundation Year; find out more.
Modules
This provides a guide of the modules that make up your course. You can find more information about how your course is structured on our Academic Advice section.
You must choose 2 x 10 credit Level 4 Opportunity modules from the Opportunity module catalogue.
What are the tuition fees
Home
-
Home, Academic Year 2024 - 2025: £9,250 per year
International
-
Overseas/International, Academic Year 2024 - 2025: £15,150 per year
What are my career prospects?
Employability is at the heart of this degree, with the curriculum strongly influenced by, and based upon, industry expectations of the skills, attributes and competencies needed for university graduates to pursue rewarding careers in different roles and sectors.
With a data science degree, you could work across a broad range of areas, such as:
- Ecommerce
- Finance
- Government
- Healthcare
- Information technology
- Scientific research.
Typical job roles include:
- Applications Architect
- Data Architect
- Data Engineer
- Data Scientist
- Enterprise Architect
- Infrastructure Architect Machine
- Learning Engineer
- Machine Learning Scientist.
Course leader
- Deputy Head of School (Creative and Digital Industries)
- Associate Professor