MSc Computing and Artificial Intelligence
This MSc develops practical and analytical skills in computing, artificial intelligence, machine learning and data engineering. It may suit graduates from any academic background who want to move into technical study or develop expertise in AI, software and data-focused fields.
About this course
This MSc combines computing fundamentals with applied artificial intelligence, machine learning and data engineering. It is designed for graduates from any subject who want to build technical knowledge in software development, programming, data management and AI applications.
You will work with Python and GitHub, explore intelligent agents and machine learning, and learn how data is stored and managed across relational, NoSQL, graph and hierarchical databases. The course also covers distributed processing, Apache Spark, Docker and Kubernetes, alongside cloud-based data management and AI pipelines in AWS or GCP ecosystems.
A substantial MSc project in computer science allows you to bring together your learning in an extended piece of work. Full-time and part-time study options are available, with study taking from 12 to 24 months.
What you will study
Core areas of study include:
- Software Development - Foundations of Statistics and Data Inference - Data Mining, Visualisation, and Actionable Intelligence - Web Technologies - Data Management Technologies - Applications of Artificial Intelligence - Programming and AI Orchestration - Distributed Processing and Data Engineering - MSc Project in Computer Science - Professional Development
You will study programming with Python and GitHub, machine learning, artificial intelligence and intelligent agents. Data-focused learning covers relational, NoSQL, graph and hierarchical databases, plus distributed processing and data engineering using Apache Spark. You will also explore containerisation with Docker and Kubernetes, and cloud-based data management and AI pipelines in AWS or GCP environments (MLOps).
Modules
Semester 1
- Software Development (core)
- Foundations of Statistics and Data Inference (optional)
- Data Mining, Visualisation, and Actionable Intelligence (optional)
- Web Technologies (optional)
Semester 2
- Data Management Technologies (core)
- Applications of Artificial Intelligence (core)
Semester 3
- Programming and AI Orchestration (core)
- Distributed Processing and Data Engineering (core)
Semesters 1 - 3
- MSc Project in Computer Science (core)
- Professional Development (core)
Assessment
Assessment is through portfolios, coursework reports and presentations.
Entry requirements
An undergraduate degree in any subject at 2:2 or above, or an equivalent qualification.
English language requirements
English language proficiency equivalent to IELTS 6.0 overall, with at least 5.5 in each component.
Careers
The course may support progression into roles and further development in AI, software development, computer science, data science and wider technology sectors.
Your next step starts with a conversation
Tell us where you are now. We will tell you honestly what your options are — in English or Persian, at no cost to you.