/MSc in AI

Provided by: Queen Mary University of London

Course Area: London

Course Code: I4U1 (FT) | I4U2 (PT)

Course Type: Masters (taught)

Start date: 01/09/2020

End date: 31/08/2021

Subjects: Artificial Intelligence, Computer Science, Data Science, Machine Learning

Price: Over £10,000

Delivery Method: Face to face

Course Overview

Artificial Intelligence (AI) is rapidly changing the way we live, work and learn. Government and industry have recognised the need for strategic development of AI; technology giants such as Google, Microsoft and Facebook have established their own AI research institutes and in 2017, the UK government announced £75 million investment in the industry. There is however a shortage worldwide of AI talents to serve the industry and to drive future research. AI jobs are amongst the best paid in the industry while a solid background in AI is strongly desired in multiple research disciplines.

 

This MSc in AI brings together Queen Mary’s teaching, research and industrial contacts to allow students to mix the different AI topics that best suits their personal requirements and future plans. Students will be offered lectures that explain the fundamental AI concepts, universal machine learning tools essential for any AI job profile, and specific practical and research skills on all five of the AI topics. Students will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL) via regular exercises and practical labs. Students will be taught by world-renowned academics in their specific subject areas, and have regular contacts with them throughout the duration of the programme.

Who is this course for

This course is for anyone looking to pursue a career in the booming field of Artificial Intelligence (AI).

What will I learn

The programme is organised in three semesters. The first semester has four modules that operate on a 3+1 scheme: 3 core modules that cover the foundations of machine learning techniques and introduction of Artificial Intelligence for Games (e.g., AlphaGo); and 1 optional module to select from three other AI topics (vision, music and language).

 

The second semester has four modules that are themed around all five AI topics offered. The module selection allows you to focus on topic-specific research or industry applications for AI. More importantly, these module options allow you to gain advanced and up-to-date knowledge on selected AI topics.

 

In the third semester, you will carry out a project on the AI topic that you want to specialise in after agreeing on a specific topic with an academic supervisor in the first semester, and completing the preparation phase over the second semester.

 

Semester 1
Machine Learning (15 credits)
Data Mining (15 credits)
Artificial Intelligence and Games (15 credits)

Further option:
Introduction to Computer Vision (15 credits)
Music Perception and Cognition (15 credits)
Natural Language Processing (15 credits)

 

Semester 2
Four options from:
Advanced Robotics Systems (15 credits)
Music Analysis and Synthesis (15 credits)
Information Retrieval (15 credits)
Artificial Intelligence (15 credits)
Music and Speech Modelling (15 credits)
Deep Learning and Computer Vision (15 credits)
Machine Learning for Visual Data Analysis (15 credits)
Multi-platform Game Development (15 credits)
Neural Networks and NLP (15 credits)

 

Semester 3
Project (60 credits)

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