Applied Artificial Intelligence MSc

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
• Programming and Maths for AI
  • This module equips you with the foundational programming and mathematical skills essential for AI study.
  • 20 credits
• Machine Learning in Practice
  • This module bridges the gap between theory and practical applications of machine learning.
  • 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
• 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

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: £1,322 (Price per 20-credit module)
• International tuition fee: £2,222 (Price per 20-credit module)
• Alumni discount: This course is eligible for an alumni discount.
• Funding: There is a range of funding available that may help you fund your studies, including Student Finance England (SFE) for UK students and various schemes for international students.
• Scholarships: The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible postgraduate students.

Teaching and Assessment

• Teaching methods focus on active student learning through lectures, seminars, workshops, problem-based and blended learning, and where appropriate practical application.
• Assessments include written exams, practical tasks, and coursework.

Supporting You

• Our Student Hub is where you’ll find out about the services and support we offer, helping you get the best out of your time with us.
• Study support, personal tutors, student advice team, and extra-curricular activities are available.

Course Location

• The course is located at our Cavendish Campus in central London, which offers state-of-the-art science and psychology labs and refurbished computer suites.

Related Courses

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