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Applied Artificial Intelligence at Northeastern University London - UCAS

Course options

2026 - 2027
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There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

What you’ll study This MSc covers the full spectrum of modern AI, from foundational principles to advanced applications. You’ll explore agentic systems, machine learning, natural language processing, analytics, autonomous decision-making, AI engineering and ethical governance frameworks. You’ll learn how AI is designed, built and applied – and how it drives change across organisations and society. Flexible pathways let you specialise in Strategy and Leadership, Analytics and Business Transformation, Development and Ethics, or Engineering and Systems, preparing you to lead, build and govern real-world AI solutions with confidence. Your learning culminates in a substantial AI Dissertation Project, where you develop a technical artefact, prototype, system or applied analysis guided by an expert supervisor. Skills that set you apart

  • Build and deploy machine learning and NLP models
  • Understand and work with agentic and autonomous AI workflows
  • Develop strong analytical and problem-solving skills
  • Apply ethical, responsible and regulatory guidelines to real systems
  • Translate business needs into effective AI solutions
  • Communicate confidently with both technical and non-technical audiences
  • Lead and manage AI-driven projects and transformation
  • Conduct rigorous independent research culminating in a dissertation
You’ll develop expertise in:
  • Applied AI methods, including machine learning, natural language processing and intelligent decision-making
  • Agentic and generative AI, understanding autonomous workflows, multi-agent systems and real-time decision architectures
  • Programming, algorithms and analytics, strengthening your ability to build, evaluate and optimise AI models
  • Data quality, curation and investigation, forming the foundation of reliable AI systems
  • Responsible and ethical AI, evaluating fairness, transparency, governance and societal impact
  • AI strategy and digital transformation, aligning AI systems with organisational needs and change agendas
  • Leadership and collaboration, working effectively across teams adopting or developing AI
  • Clear communication, presenting technical and strategic insights to specialist and non-specialist audiences
  • Independent research and innovation, culminating in an applied AI dissertation or technical artefact
  • This blend of technical skill, critical thinking and strategic understanding prepares you for impactful roles across the AI sector.
Graduates are equipped to work across a wide range of industries adopting AI technologies, including:
  • Artificial intelligence & machine learning
  • Data analytics & automation
  • Technology & software engineering
  • Consulting & digital transformation
  • Financial services & fintech
  • Government, public policy & regulation
  • Healthcare, biotech & medical AI
  • Retail, logistics & operations
  • Creative industries & generative technologies
  • Sustainability, environment & smart systems
  • Startups and high-growth innovation environments
Career paths and roles Depending on your pathway – technical, analytics, leadership or ethics – you may progress into roles such as: Technical & Development Roles
  • AI Engineer
  • Machine Learning Developer
  • AI Software Engineer
  • Applied NLP or ML Specialist
Ethics, Policy & Governance Roles
  • AI Ethics Specialist
  • Responsible AI Officer
  • AI Policy Analyst
  • AI Risk & Compliance Analyst
Strategy, Product & Transformation Roles
  • AI Product Manager
  • Digital Transformation Consultant
  • AI Strategy Lead
  • Innovation & Automation Manager
  • Technology Project Manager
These roles span sectors that are rapidly expanding their use of intelligent systems, giving graduates strong career prospects in an AI-driven economy.

Modules

Agentic and Generative Artificial Intelligence; Artificial Intelligence and Data Ethics; Academic and Professional Enquiry Methods; Artificial Intelligence Dissertation Project; Algorithms and Analytics OR Software Engineering and Program Design; Postgraduate In-the-Field Experiential Project; Machine Learning and Natural Language Processing;

How to apply

International applicants

Northeastern University London is a licensed Tier 4 Sponsor. More information for international applicants can be found at www.nulondon.ac.uk/hubs/international-students/

Entry requirements

Academic qualifications: We typically make offers to applicants who hold a UK undergraduate degree with at least a second-class (2:2) honours (or international equivalent). Professional experience: We also welcome applications from mature students and professionals who may have been out of formal education but can demonstrate relevant professional experience or equivalent qualifications. Each application is reviewed on an individual basis and assessed through the application form, reference, and personal statement.

Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

No additional fees or cost information has been supplied for this course, please contact the provider directly.

Sponsorship information

Scholarships are available https://www.nulondon.ac.uk/postgraduate-fees-and-funding/

Applied Artificial Intelligence at Northeastern University London - UCAS