Course summary
Are you ready to launch or accelerate your career in data science and AI? The demand for qualified data scientists far exceeds the current supply, and the industry faces a significant global skills gap. Our online MSc Data Science programme is designed to bridge this gap by providing you with the relevant practical skills and expertise needed to excel in data-related roles, giving you a pathway to establishing a fulfilling and potentially lucrative career. What you'll learn Our data science degree covers everything from fundamental mathematical concepts to advanced topics like artificial intelligence, machine learning, deep learning, and cloud computing. You'll master essential tools and programming languages such as Python, in addition to gaining proficiency in software tools like Jupyter Notebooks and Tableau. You’ll also tackle real-world scenarios through our programme's individual modules. Whether you're exploring the ethical and legal constraints of data science or delving into the intricacies of machine learning and deep learning, you'll be immersed in practical applications. Our "Learn by Doing" philosophy ensures you can apply your knowledge to make meaningful business decisions using real data sets. Ultimately, you'll gain genuine insight into how data science operates, from data gathering and processing to analysis for operational and strategic purposes -- developing a strong understanding of the ethical and legal considerations that shape the role of data science professionals.
Modules
Programming for Data Science (20 credits) Mathematics for Data Science (20 credits) Big Data and Cloud Computing (20 credits) Machine Learning (20 credits) Artificial Intelligence and Neural Networks (20 credits) Data Visualisation (20 credits) Advanced Computing Project (60 credits)
Assessment method
The way we assess our masters students provides you with the opportunity to demonstrate your strengths and abilities. That’s why we choose a range of methods to keep track of your progress. These include: Portfolio development Case study reports Risk assessments Business Transformation Project
Entry requirements
Standard entry requirements: A 2.2 Honours degree, or equivalent, in a numerate subject (majority of it would need to be maths based. Examples include maths, finance, computing, science, engineering. Typical non-standard entry requirements: A minimum of 3 - 5 years of relevant work experience within a data environment, or equivalent. Type of relevant work experience: Maths, finance, engineering, science, data analysis etc. Need to have worked with maths and or data analysis in their current role to be eligible. Not just using basic level Excel (Power Query excel experience may be accepted), but heavily data based where they can evidence a strong Mathematics starting point to do this degree.
Fees and funding
Tuition fees
| EU | €15000 | Year 1 |
| International | €15000 | Year 1 |
| England | €15000 | Year 1 |
| Northern Ireland | €15000 | Year 1 |
| Scotland | €15000 | Year 1 |
| Wales | €15000 | Year 1 |
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Provider information
Arden University
Arden House
Middlemarch Park
Coventry
CV3 4FJ