Artificial Intelligence Applications and Innovation MSc

Program Overview

This MSc in Artificial Intelligence Applications and Innovation equips students with fundamental AI knowledge, practical skills, and business acumen. They delve into core AI concepts, cultivate hands-on expertise, and explore the diverse applications of AI across industries. Graduates are prepared for leadership roles in developing AI technologies and driving innovation in both business and academia.

Program Outline

Degree Overview:

This MSc program aims to equip students with the fundamental knowledge and practical skills needed to become leaders in AI technologies and business. It focuses on harnessing AI innovations for real-world impact and entrepreneurial opportunities, preparing students for careers in both industry and academia. The program emphasizes:

• Understanding AI fundamentals: Students will delve into the core of AI and machine learning, exploring the intricate world of deep learning.
• Cultivating hands-on skills: The program provides practical experience in AI technologies, allowing students to develop the skills needed to create AI solutions and deploy AI applications in real-world settings.
• Exploring diverse AI applications: Students will examine the application of AI across various industries, including healthcare, finance, and robotics.
• Developing AI-driven business innovation: The program fosters entrepreneurial acumen, equipping students to spearhead AI ventures and drive innovation within established corporations.

Core Modules:

• Group Project on AI Ventures and Ethics: This project-oriented, team-driven module explores AI applications in finance, health, and other areas.
Students learn from industry leaders and culminate the module with a business proposal and technical demonstration.

Optional Modules:

Students choose seven optional modules in total:

• Group A (at least two modules):
• Python and Machine Learning:
Covers machine learning theory, algorithms, and applications, emphasizing Python programming proficiency for practical problem-solving.
• Deep Learning: Masters the fundamentals and advanced methodologies of deep learning, connecting theory to real-world issues.
• Group B (four or five modules):
• Quantum AI (Independent Study):
Encourages independent study in Quantum AI, exploring advanced topics such as variational quantum algorithms, quantum data learning, and advanced quantum error correction.
• Internet of Things and Applications: Studies Internet of Things platform development, data acquisition from sensors, analysis, actuations, and data mining insights.
• Fundamentals and Innovative Applications of Robotics: Explores robotics theory and practice, emphasizing innovative applications and hands-on experience with Robot Operating System (ROS) for solving real-world problems.
• Trustworthy Artificial Intelligence in Medical Imaging: Explores the crucial aspect of AI trustworthiness in medical imaging, delving into cutting-edge technological development and research, learning about deep learning techniques for enhanced reliability.
• Machine Learning for Actionable Decision-Making in Healthcare: Develops healthcare-focused machine learning models, addressing unique challenges in clinical data, risk stratification, precision medicine, and interpretability.
• Machine Learning for Streamed Data: Explores rough path theory, reservoir computing, and deep learning models, developing skills in applying machine learning to streamed data with practical Python implementations and domain-specific integration.
• Machine Learning for Tackling Climate Change: Discovers machine learning's role in climate change adaptation and mitigation, covering greenhouse gas reduction, climate modelling, and AI solutions' limitations and advantages.

Individual Project/Internship:

This is the program's pinnacle, where students create AI technologies for an application while exploring entrepreneurship, ethics, and social impact. Students are encouraged to bring original thinking to a research or application area of interest to them. They have the opportunity to develop interdisciplinary projects with potential business cases.

Assessment:

Methods:

• Coursework
• Examinations
• Practical
• Individual research project
• Oral presentations
• Written examinations
• Written reports
• Essays

Balance:

• 20% Coursework
• 19% Examinations
• 61% Group & individual projects / internship

Teaching:

Methods:

• Lectures
• Laboratory work
• Tutorials
• Individual and group projects
• Independent study
• Virtual learning environment
• Presentations

Balance:

• 12% Lectures and tutorials
• 88% Independent study

Faculty:

The program is delivered by world-leading experts from Imperial's prestigious AI research and teaching initiative, I-X. This includes faculty from the Imperial College Business School, Department of Computing, Department of Electrical and Electronic Engineering, and Department of Mathematics.

Careers:

Potential Career Paths:

• Leadership roles in multinational tech corporations
• Prestigious research positions
• Designing AI solutions for various sectors (finance, healthcare, robotics)
• Spearheading AI ventures
• Driving innovation within established corporations

Opportunities:

• Acquire skills to design AI solutions and provide a key role in sectors where AI innovation is paramount.
• Develop entrepreneurial acumen, being equipped to spearhead AI ventures and drive innovation within established corporations.
• Navigate the AI landscape ethically, making you a responsible and sought-after AI professional.

Outcomes:

• Master AI fundamentals and unlock global career avenues.
• Acquire skills to design AI solutions and provide a key role in sectors like finance, healthcare, and robotics, where AI innovation is paramount.
• Develop entrepreneurial acumen, being equipped to spearhead AI ventures and drive innovation within established corporations.
• Imperial College London is ranked 1st in the UK for Computer Science and Informatics based on the Research Excellence Framework (REF) 2021.
• The program is part of I-X, Imperial's cross-college strategic AI initiative.
• Students will have the opportunity to showcase their AI idea to leading venture capitalists and innovation investors.

Tuition Fees:

• Home fee: £39,000
• Overseas fee: £39,000

Payment Terms:

• Fees can be paid in installments.
• A postgraduate early payment discount is available.
• There is a postgraduate application deposit.