BSc (Hons) Data Science

This course aims to produce multi-skilled, highly competent graduates who are equipped to make significant contributions to their career field and who understand the implications of their work, both for themselves and for society as a whole. 
The course has three integrated strands which develop mathematical foundations, computational thinking, and engineering skills. It's the combination of these three areas that make graduates attractive to employers, enabling an immediate contribution when moving into employment.

You'll be provided with a solid foundation in the principles and practices of data science, including relevant computer science components such as coding and machine learning, and mathematical areas such as probability, statistics and calculus. Key aspects of modern data science are covered, from the theoretical building blocks of linear algebra and algorithmics, to real-world implementations and discussion of the wider impacts that data science has on society.

You'll develop the technical skills needed to critically analyse, mine, and manage different kinds of data in order to learn and discover interesting patterns. You'll learn how to make actionable conclusions from those assessments, while participating effectively in multidisciplinary teams. Study culminates in a focused research project in the field of data science which develops the skills to contribute professionally to solving complex commercial and industrial engineering problems.

Course content

• All students will study our core topics in computer science, which we have designed to be consistent with the Association for Computing Machinery (ACM) curriculum guidelines. These core topics provide the fundamental knowledge that all computer science graduates should possess, and the foundation to study more flexibly in the third year.

Year 1
Core modules

• Software 1: Foundations of Programming for Computer Science
• Introduction to Probability and Statistics
• Foundations and Calculus
• Software 2: Object Oriented Data Structures and Algorithms
• DATA: Introduction to Data Science
• Multivariable Calculus and Matrices

Academic integrity module

• In addition to the above you will also need to complete our online Academic Integrity module.

Year 2
Core modules

• Systems and Devices 2: Operating Systems, Security, and Networking
• Engineering 1: Software and Systems Engineering
• Probability and Markov Chains
• Intelligent Systems: Machine Learning and Optimisation
• Linear Algebra
• Statistical Inference and Linear Models

Year 3
Core modules

• Computer Science project or Mathematics project
• Governance in Data Science
• Cloud-Based Data Analysis

Option modules

You will study two option modules. Examples can be found below. Some option module combinations may not be possible. The options available to you will be confirmed after you begin your course.

• AI Problem Solving with Search and Logic
• Autonomous Robotic Systems Engineering
• Computer Vision and Graphics
• Cryptography Theory and Practice or Cryptography
• Engineering 2: Automated Software Engineering
• Intelligent Systems: Probabilistic and Deep Learning
• Interaction Design and Evaluation
• Qualitative Approaches to Investigating UX
• Quantum Computation
• Decision Theory and Bayesian Statistics
• Generalised Linear Models
• Mathematical Finance in Continuous Time
• Mathematical Finance in Discrete Time
• Multivariate Data Analysis
• Numerical Analysis
• Operations Research
• Statistical Pattern Recognition
• Time Series

Elective modules

• You may be able to replace one option module with an elective module, studying a complementary subject, a language or an interdisciplinary topic.

Teaching and assessment

• You’ll study and learn with academics who are active researchers, experts in their field and have a passion for their subjects. Our approach to teaching will provide you with the knowledge, opportunities, and support you need to grow and succeed in a global workplace.

Teaching format

• A typical week will involve about 10-15 hours of scheduled teaching time. Our courses are based on a series of lectures with associated laboratory sessions, programming classes and tutorials.
• Throughout the course, you will have a personal supervisor responsible for guiding your studies. In addition to any timetabled sessions, you will meet with your supervisor regularly, and you can also go to them at any time should you have any issues, academic or personal. There are problem classes to help you put learning from lectures into practice and regular project supervision meetings for your individual project.
• You will also undertake learning outside of the scheduled timetable. This can be through working in the labs, through reading recommended materials or by working through problems. Consequently, you'll need to be self-motivated, self-disciplined and willing to learn outside regular classes.
• As you progress through the course you will develop your skills to become a more independent learner. You'll also spend time working on your individual research project later on in the course, in addition to timetabled activity.
• In the UK, full-time students are expected to spend 1,200 hours a year learning. That's about 40 hours of classes and independent study each week during semesters. Everyone learns at a different rate, so the number of hours you spend on independent study will be different to other students on your course.

Facilities

• Built to the highest specifications, the Department of Computer Science is packed with cutting-edge facilities housed in a modern, self-contained building.
• Computer Science houses four software and two hardware laboratories which you will be able to use depending on the topic of your third year project. These facilities are professional grade and used by our research teams so, depending on your interests, you'll get first hand exposure to these environments.
• The Department of Mathematics is a community of mathematicians from all over the world, engaged in world-class research and committed to excellence in teaching with a special emphasis on small groups and a friendly atmosphere.

Careers and skills

• The move towards a digital economy creates demand for computer scientists and software engineers across a broad section of employers, so the skills you develop here will make you attractive to many organisations. Most of our graduates go into the field of IT/computing, followed by financial services, some undertake further study (eg PhD) and others go straight into industry (for example working for IBM, BAE Systems).
• Many of our graduates are employed by software and electronics industries, but the continuing expansion of the use of computers in commercial and financial operations means that you will be able to find employment in other industries - and here your sharpened numeracy and analytical skills will have prepared you well.
• Read some profiles of our past students and find out how their degree from York helps them to do jobs in organisations as diverse as Mars Inc and Cancer Research UK. Other companies that York graduates have gone on to work for include Amazon, BAE Systems, Morgan Stanley, G Research, Thales, the Civil Service, M&G Investments, Ubisoft, Rapita Systems, Sky, BT, Raspberry Pi, IBM, JP Morgan, Hut Group and Automaton Games.

Career opportunities

• Computer programmer
• Software engineer
• Software developer
• Business analyst
• Research scientist
• Network manager
• IT Systems manager

Transferable skills

• At York, you will gain a broad understanding of all of the essential scientific principles, engineering techniques and practices in computer science. This allows you to be flexible and adapt quickly in any field that you wish to go into. 

More specifically, we can identify four main skill areas:

• Analytical skills
• Research skills
• Management skills
• Communication skills