There is a demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies.
Study topics in big data management, data protection and data ethics, statistical modelling, machine learning, deep learning, computer vision, natural language processing, generative AI and reinforcement learning.
Explore how data science can be used to extract meaningful insights from both structured and unstructured data, leveraging concepts and tools from mathematics, statistics, computer science, machine learning and related disciplines.
Learn about computational intelligence and how it plays a pivotal role in solving complex problems and simulating human-like intelligence in computational systems.
Start dates:
An honours degree 2:2 or above (or international equivalent) in a relevant discipline such as computer science, mathematics, statistics or engineering.
We recognise a breadth of qualifications, speak to one of our advisers today to find out how we can help you.
On successful completion of this course, you should be well qualified to apply your technical, research, programming, problem-solving and analytical skills across various sectors including technology, industry, business and government.
There could be career opportunities in AI research and development, machine learning, data management and data analysis. Potential employers include AI research institutions, major technology companies, tech startups, data science teams within businesses and government agencies, and professional consultancy firms.
Machine Learning and Statistical Modelling — 30 credits
Deep Learning and Computer Vision - 30 credits
The Data Science Professional — 30 credits
Generative Al and Reinforcement Learning — 30 credits
MasterS with professional placement
Individual Research Project — 60 credits
Masters and Taught Courses at Coventry University Introduction Coventry University is a provider of world-class teaching, learning and impactful rese...