Open University

BSc (Honours) in Data Science

This degree has three stages, each comprising 120 credits.

• In Stage 1, you’ll study four 30-credit modules.
• In Stage 2, you’ll study four 30-credit modules.
• In Stage 3, you’ll study two 30-credit modules and choose two 30-credit option modules.

Stage 1 (120 credits)

You'll study all four of the following:

• Introducing Statistics (M140)
• Introduction to Computing and Information Technology 1 (TM111)
• Essential Mathematics 1 (MST124)
• Introduction to Computing and Information Technology 2 (TM112)

Stage 2 (120 credits)

You'll study all four of the following:

• Analysing Data (M248)
• Algorithms, Data Structures, and Computability (M269)
• Mathematical Methods (MST224)
• Practical Modern Statistics (M249)

Stage 3 (120 credits)

You'll study both of the following:

• Applied Statistical Modelling (M348)
• Machine Learning and Artificial Intelligence (TM358)

Additionally, you'll choose two from the following options:

• Applications of Probability (M343)
• Computational Applied Mathematics (MST374)
• Data Management and Analysis (TM351)
• Graphs, Games, and Designs (MST368)
• Interaction Design and the User Experience (TM356)
• Mathematical Statistics (M347)

Assessment

Our assessments are all designed to reinforce your learning and help you show your understanding of the topics. The mix of assessment methods will vary between modules.

Computer-Marked Assignments

• Usually, a series of online, multiple-choice questions.

Tutor-Marked Assignments

• You’ll have a number of these throughout each module, each with a submission deadline.
• They can be made up of essays, questions, experiments or something else to test your understanding of what you have learned.
• Your tutor will mark and return them to you with detailed feedback.

End-of-Module Assessments

• The final, marked piece of work on most modules.
• Modules with an end-of-module assessment won’t usually have an exam.

Exams

• Some modules end with an exam. You’ll be given time to revise and prepare.
• You’ll be given your exam date at least 5 months in advance.
• Most exams take place remotely, and you will complete them at home or an alternative location.
• If a module requires you to take a face-to-face exam, this will be made clear in the module description, and you will be required to take your exam in person at one of our exam centres.

Knowledge and understanding

On completion of this degree, you will have knowledge and understanding of:

• A range of simple and more advanced methods for analyzing statistical data (including medical applications data, time series data, and multivariate data), working with statistical models, and carrying out statistical inference (including in particular methods for linear and generalized linear models, and Bayesian methods)
• Calculus, differential equations, linear algebra, multivariable calculus, and vector calculus
• The fundamental principles, concepts, and techniques underlying computing and IT, and the range of models used to support the analysis and design of computing and IT systems
• The range of situations in which computing and IT systems are used in data science and the possibilities and limitations of such systems
• Machine learning and artificial intelligence
• The ethical and legal issues associated with data science
• A selection (depending on your options) of advanced topics including advanced data management and analysis, graph theory, network analysis, mathematical methods, applied probability, mathematical statistics, and interactive design.

Cognitive skills

On completion of this degree, you will be able to:

• Use your judgement in applying and selecting a wide range of mathematics and statistics tools and techniques to solve real-world problems
• Construct appropriate mathematical and statistical models and draw justifiable inferences in qualitative and quantitative problem-solving skills
• Reason with abstract concepts
• Apply and critically evaluate key computing and IT concepts in a range of contexts
• Select and apply appropriate techniques and tools for abstracting, modelling, problem-solving, designing and testing computing and IT systems, and be aware of the limitations involved.

Practical and professional skills

On completion of this degree, you will be able to:

• De is an independent learner, able to acquire further knowledge with minimal guidance or support
• Use appropriate professional tools, including programming languages, to support your work
• Apply mathematical, statistical and computational concepts, principles and methods
• Analyse and evaluate problems and plan strategies for their solution
• Analyse, design, evaluate and/or test models and systems, using appropriate simulation and modelling tools as appropriate
• Identify and address the ethical, social and legal issues that may arise during the development and use of computing and IT systems.

Key skills

On completion of this degree, you will be able to demonstrate the following skills:

• Communicate information, arguments, ideas and issues clearly and in appropriate ways, bearing in mind the audience for and the purpose of the communication
• Find, assess and apply information from a variety of sources, using information technology where appropriate
• Select, and use accurately, appropriate numerical and analytical techniques to solve problems
• Prepare mathematical, statistical and computational content for a range of purposes, which may include writing for both specialist and non-specialist audiences
• Recognise and understand a range of technological and practical problems and select suitable techniques for solving them.

Skills for career development

The ability to analyse complex data sets is a much sought-after skill in the modern workplace. The degree will equip you with knowledge of data analysis and modelling from statistics, applied mathematics and computer science. In addition, you’ll develop important transferable skills such as communication, time management and problem-solving.

Career relevance

Data scientists are highly sought after in virtually all workplaces. The use of data science in social media, online commerce and government has revolutionised the digital economy, with employers across both the public and private sectors now recruiting data scientists to identify and solve complex business problems. Data scientists are at the heart of supporting strategic and operational decision-making. They are needed in all areas of employment including business intelligence, management, biology, economics, education, engineering, environment studies, finance, government, logistics, medicine, meteorology, market research, sport and multinational businesses.

With our unique approach to distance learning, you can study from home, work or on the move.

You’ll have some assessment deadlines to meet, but otherwise, you’ll be free to study at the times that suit you, fitting your learning around work, family, and social life.

For each of your modules, you’ll use either just online resources or a mix of online and printed materials.

Each module you study will have a module website with

• A week-by-week study planner, giving you a step-by-step guide through your studies
• Course materials such as reading, videos, recordings, and self-assessed activities
• Module forums for discussions and collaborative activities with other students
• Details of each assignment and their due dates
• A tutorial booking system, online tutorial rooms, and your tutor’s contact details
• Online versions of some printed module materials and resources.