Program Overview

Applied Artificial Intelligence MSc

Overview

The Applied Artificial Intelligence MSc will equip you with essential techniques and practical skills, preparing you to tackle real-world challenges and contribute to the growing field of Artificial Intelligence.

Course Structure

Core Modules

• Foundations of Artificial Intelligence
  • This module will provide you with an introduction to the core concepts and techniques of artificial intelligence, from search algorithms, knowledge representation, and machine learning, to the ethical considerations of AI in society.
  • 20 credits
• Applied AI and Industrial Decision Support Systems
  • This module explores AI-driven decision support systems, their role in diverse industries, and their capability to enhance human decision-making.
  • 20 credits
• Deep Learning and Neural Networks
  • In this module, you’ll begin with foundational concepts and progress to cutting-edge deep learning techniques covering perceptron, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and attention models.
  • 20 credits
• Machine Learning in Practice
  • This module bridges the gap between theory and practical applications of machine learning.
  • 20 credits
• MSc Applied AI Project
  • This module is the culmination of the course requiring you to demonstrate your learning by identifying critical challenges, conducting rigorous literature reviews, and designing innovative AI solutions.
  • 60 credits
• Programming and Maths for AI
  • This module equips you with the foundational programming and mathematical skills essential for AI study.
  • 20 credits

Option Modules

• Applied Computer Vision
  • This module equips you with the foundational algorithms, tools, and techniques needed to design, implement, and assess computer vision applications across various domains.
  • 20 credits
• Big Data and Cloud Computing
  • This module focuses on distributed data storage, processing frameworks, and the design and deployment of scalable cloud-native applications.
  • 20 credits

Entry Requirements

• A minimum of a lower second class honours degree (2:2) in a science, mathematics, computer science, or engineering discipline, with some exposure to the use of IT.
• Applications will also be considered from individuals who do not have a first degree in these subjects but have gained significant industry experience in data science or software development.
• If your first language is not English you should have an IELTS 6.5 with at least 6.5 in writing and no element below 6.0.

Fees and Funding

• UK tuition fee: £11,900 (Price per academic year)
• International tuition fee: £20,000 (Price per academic year)
• Alumni discount available
• Funding schemes available for international students
• Scholarships available for eligible postgraduate students

Teaching and Assessment

• Teaching methods include lectures, seminars, workshops, problem-based and blended learning, and where appropriate practical application.
• Assessments include written exams, practical, and coursework.

Supporting You

• Study support – workshops, 1-2-1 support and online resources to help improve your academic and research skills
• Personal tutors – support you in fulfilling your academic and personal potential
• Student advice team – provide specialist advice on a range of issues including funding, benefits and visas
• Extra-curricular activities – volunteering opportunities, sports and fitness activities, student events and more

Course Location

• Cavendish Campus, central London

Related Courses

• Data Science and Analytics MSc
• AI, Data and Communication MA
• Big Data Technologies MSc