Online Computing Science 2025-2026

This course will introduce you to the Python programming language and teach you how to use Python to process and visualise data using the popular numpy, pandas and dash libraries. 

This course will introduce you to the Python programming language and teach you how to use Python to process and visualise data using popular libraries such as numpy, pandas and dash.

This course will deliver the most sophisticated Machine Learning methodologies and algorithms which would be illustrated across a wide range of applications including but not limited to images, videos, health, time series data, language processing, etc. This course provides students with the Machine Learning principles for continuing learning and working in the area of Data Science and Artificial Intelligence. 

This course will be of interest to anyone who wishes to learn to design and query databases. The course aims to teach the material using case studies from real-world applications. You will develop a critical understanding of the principal theories, principles and concepts, such as modelling techniques used in the design, administration and security of database systems. You will also learn core theoretical concepts such as relational algebra, file organisation and indexing. At the end of this course you will be able to design and build Web and cloud-based databases and have a critical understanding of how database-driven applications operate.

This course will introduce you to the Python programming language and teach you how to use Python to process and visualise data using the popular numpy, pandas and dash libraries. 

The global autonomous systems market is expected to be valued at over £13 billion by 2025, involving both software systems and robots. Such autonomous systems act to achieve goals with no human intervention, and are already found in Tesla's self-driving cars, NASA space probes and systems such as Amazon's Echo. This course provides the student with a solid grounding in the theory and tools which underpin such systems, teaching them both how to develop such systems, and use them effectively as part of a larger product.

This course aims to make students familiar with basic data mining and visualisation techniques and software tools. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time series analysis, and many other techniques. This course will also cover text mining and qualitative modelling. Through this course students will be able to analyse real-world datasets in various domains and discover novel patterns from them. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.