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Lancaster University: Statistics and Artificial Intelligence
| Institution | Lancaster University View institution profile |
|---|---|
| Department | School of Mathematical Sciences |
| Web | www.lancaster.ac.uk |
| pgadmissions@lancaster.ac.uk | |
| Telephone | +44 (0)1524 592032 |
| Study type | Taught |
MSc
Summary
Drive the future of AI with advanced statistical and machine learning expertise. With our ultra-modern curriculum, the MSc in Statistics and Artificial Intelligence will empower you to go beyond off-the-shelf AI tools. You’ll gain a deep understanding of the powerful statistical techniques underpinning modern AI, enabling you to apply and modify these models for real-world challenges.
Lancaster University’s School of Mathematical Sciences is at the forefront of mathematical AI research, which means you will learn from leaders in this field. We have recently been awarded major grants of £12 million and £9 million relating to AI and machine learning to establish the Mathematics for AI and Real-World Systems (MARS) group and lead the Probabilistic AI Hub.
Who is this programme for? Where other AI and data science Master’s focus on computing and engineering elements, we bring a new perspective by teaching the statistical foundations behind AI models and machine learning. So, if you have a strong maths background and are interested in being at the forefront of AI technology, the MSc Statistics and Artificial Intelligence is for you.
Looking ahead to employability The advanced level of skills and knowledge that you gain throughout the MSc will make you highly sought after by employers: - Develop core skills in statistical theory, algorithms, and computing
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Learn how to communicate complex data insights effectively, preparing you for a successful career in data science or AI
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Gain hands-on experience with neural networks, deep learning, and state-of-the-art Bayesian inference, ensuring that you can tackle complex problems across various domains
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Through group project work you will develop your applied statistical and methodological skills
What to expect There are three phases to your learning. You will first strengthen your core knowledge and skills in statistical methods and inference. Topics covered are frequentist and Bayesian inference, data analysis, generalised linear models, statistical computing, and communication. These topics provide the foundations on which to build an understanding of the mechanics of AI and machine learning.
In the second phase you will delve deeper, taking advanced modules in supervised and unsupervised learning, deep learning and statistical models for complex processes. As well as learning the statistical and computational ideas used to infer structure in these models, you will gain practical insight by applying them to data.
In phase three you will complete an independent research project on a topic of your choice, supervised by experts from our School of Mathematical Sciences. You might progress your understanding of a topic covered in a module, investigate a topic not covered by one of the modules, or undertake an extended data analysis.
Upon graduation, you will be equipped to lead in the development and application of AI technologies across a range of industries.
Three things we would like you to know - We emphasise hands-on work where you put theories to the test with practical challenges and computer lab sessions
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Our maths and AI researchers are pioneering scientific advances. We develop revolutionary statistical and machine learning methods for researchers, businesses, and the public sector
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We have been successfully delivering contemporary statistics Master's programmes for over 20 years and many of our graduates are now leaders in their fields
| Level | RQF Level 7 |
|---|---|
| Entry requirements | 2:2 Hons degree (UK or equivalent) in Mathematics or Statistics. We may also consider non-standard applications where you have studied a degree in other quantitative subjects that include courses in probability, statistics, linear algebra, and calculus. You should clearly be able to demonstrate how your skills have prepared you for relevant discussions and assessments during postgraduate study. |
| Location | Main Site Admissions Bailrigg Lancaster LA1 4YW |
Summary
Shape the future of AI with advanced statistical and machine learning expertise. The MSc in Statistics and Artificial Intelligence at Lancaster University is your gateway to a future in AI, machine learning, and data science. Mastering the statistical foundations behind AI models is essential to driving innovation. At Lancaster University, our MSc in Statistics and Artificial Intelligence empowers you to go beyond using off-the-shelf AI tools. You’ll gain a deep understanding of the powerful statistical techniques underpinning modern AI, enabling you to apply and modify these models for real-world challenges. Why Choose Lancaster's MSc in Statistics and AI?
Our programme offers a unique blend of rigorous statistical theory and cutting-edge AI applications. You’ll not only learn how to apply machine learning techniques but also gain insights into the construction of these algorithms. With a strong foundation in statistics, you’ll be equipped to modify and enhance AI models, preparing you for high-demand roles across various industries or further academic study. With a blend of statistical theory and practical AI skills, you’ll be equipped to lead in the development and application of AI technologies across a range of industries. Start your journey with us and shape the future of AI.
- Who is This Programme For?* This MSc is ideal for students with a strong background in quantitative disciplines, such as mathematics. Whether you’re looking to enter the AI industry or advance into academic research, this course will provide the tools you need to succeed.
Programme Highlights
Term 1: Build Your Foundation in Statistical Inference and Algorithms Start by developing core skills in statistical theory, algorithms, and computing. This term provides the essential knowledge you need to understand the mechanics of AI and machine learning models. You'll also learn how to communicate complex data insights effectively, preparing you for a successful career in data science or AI.
Term 2: Advanced Training in Machine Learning In the second term, you’ll dive deep into machine learning. Go beyond simply applying pre-built models—understand the mathematical and computational ideas behind them. You’ll cover both supervised learning methods for tasks like prediction and classification, and unsupervised learning techniques for clustering and anomaly detection. You’ll also gain hands-on experience with neural networks, deep learning, and state-of-the-art Bayesian inference, ensuring you can tackle complex problems across various domains.
Term 3: Individual Dissertation Project During the summer, you’ll undertake an independent research project on a topic of your choice, supervised by experts from Lancaster’s School of Mathematical Sciences. These projects may even involve collaboration with industry partners, providing real-world context to your learning. This research will give you the opportunity to apply your newly acquired skills in machine learning and statistics, culminating in a dissertation that showcases your expertise.
| Level | RQF Level 7 |
|---|---|
| Location | Main Site Admissions Bailrigg Lancaster LA1 4YW |
Lancaster University is home to a dynamic postgraduate community and offers a wealth of both taught and research study options across a wide range of subject areas. Studying at Lancaster is all about broadening your horizons, finding new perspectives and discovering new experiences. By living and studying with students and staff from over 130 countries students join a global community and have the opportunity to make international connections.
We are proud to be highly ranked in three major UK league tables. We’ve also been awarded 5 Stars for overall performance in the globally renowned QS World Ratings. The …
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