This master’s qualification, with its focus on hands-on learning, will give you the skills you need to be able to analyse and interpret data to make business decisions. Across modules and topics such as machine learning, artificial intelligence, distributed and cloud computing, and programming for data science, you will see how modern businesses use a range of tools and platforms to manage and exploit ‘big data’. Alongside specialist knowledge, you’ll also develop your communication, planning and decision-making ability.
We will consider you as an individual and take into account all elements of your application, not just your qualifications. We are looking for breadth and depth in your current studies and enthusiasm for the subject you wish to study.
Standard entry students will need to have an undergraduate degree in a numerate subject where many of the modules were mathematics-based. Examples include, but are not limited to maths, finance, computing, science, and engineering. Or an equivalent degree with 18 months of relevant computing work experience. Transfer applicants will be required to go through the Recognition of Prior Learning process (RPL) whilst non-standard applicants will need to evidence their relevant work experience; your work experience should be in a data-based role, for example, finance, engineering, science, data analysis, etc.
Year 1 – Level 4
| Programming for Data Science (Compulsory) | Mathematics for Data Science(Compulsory) |
| Big Data and Cloud Computing (Compulsory) | Machine Learning (Compulsory) |
| Artificial Intelligence and Neural Networks (Compulsory) | Data Visualization (Compulsory) |
| Advanced Computing Project (Compulsory) |
The way we assess our students provides you with the opportunity to demonstrate your strengths in a variety of ways. That’s why we choose a range of different methods to keep track of your progress. The MSc Data Science programme adopts a modern assessment approach designed to immerse you in practical, real-world challenges. Assessment methods include portfolio submissions featuring tangible assets created during each course module using industry-standard tools. By the programme’s end, you’ll have a professional portfolio demonstrating your data science expertise, providing compelling evidence of your skills.
The programme is taught using face-to-face learning. Students will have access to IVY tools and resources as well as Arden University’s iLearn/VLE to complete their studies/modules. Support will be provided by local and link tutors at IVY and AU.