What is the total credit value of the MSc in Artificial Intelligence?
The MSc comprises 120 credits: 10 foundation credits, 60 compulsory core credits, 40 elective credits, and a 10-credit Applied AI Capstone.
Do I get to choose my AI specialisation?
The programme provides eight elective options, from which learners choose four. This allows you to develop a pathway around areas such as AI agents, robotics, quantum computing, data engineering, business intelligence, AI quality assurance, AI product management, or AI strategy.
Does the programme cover Generative AI?
Yes. Generative AI is integrated across the curriculum, including Generative AI & LLM Engineering, Deep Learning & Neural Networks, NLP & Prompt Engineering, AI Engineering and selected advanced pathways.
Will I learn about AI agents?
Yes. Learners selecting AI Architecture & Agents can study AI architecture and agent development through AI+ Architect, AI+ Agent, and Azure-focused AI agent learning.
Does the MSc include Microsoft technologies?
Yes. The curriculum incorporates bundled learning involving technologies and environments such as Microsoft Azure, Microsoft Fabric, Power BI, Azure Databricks, Azure Database for PostgreSQL, GitHub Copilot, and GitHub Actions.
Does the programme cover responsible AI?
Yes. A compulsory Responsible AI, Ethics & Governance module explores AI ethics, policy, governance, and responsible implementation.
Is there a practical project?
Yes. The programme concludes with a 10-credit Applied AI Capstone, where learners address a real problem end to end and submit a report together with working code or a deployed model.
Who is this MSc suitable for?
The programme can be particularly relevant for software developers, IT professionals, data professionals, AI and machine learning professionals, technology managers, digital transformation professionals, entrepreneurs, product leaders, and professionals seeking to build careers around AI.
What career opportunities can I explore after the programme?
Depending on your previous experience and skills, potential pathways include AI Engineer, Machine Learning Engineer, Generative AI Engineer, LLM Engineer, NLP Engineer, MLOps Engineer, Data Scientist, AI Architect, AI Product Manager, AI Strategy Consultant, AI Transformation Lead, and other emerging AI roles.