Data Science and Artificial Intelligence (Conversion Programme) MSc

Program Overview

This MSc program in Data Science and AI is designed for individuals seeking expertise in these fields. It provides a comprehensive foundation in programming, statistics, and AI techniques, preparing graduates for careers as data science specialists in various industries. The program includes two preparatory modules, six compulsory modules, and a final year project, ensuring a thorough understanding of the principles and applications of data science and AI.

Program Outline

Outline:

Please note that this course will commence on Monday, 9th September, earlier than other Queen Mary courses. This degree programme aims to help learners without strong backgrounds in programming or statistics to acquire a level of skill in these areas, before learning to apply them to specialist AI techniques. These two intensive preparatory modules will allow you to acquire the pre-requisite skillset in programming and statistics, before diving into more specialised modules. Before starting the programme, you can complete a free online short course, Get Ready for a Masters in Data Science and AI, developed by a collaborative partnership of leading higher education institutions, including Queen Mary.

Structure:

Two preparatory modules. Six compulsory modules. Compulsory final year project. Projects will either be significantly development based or have a research focus that will require you to undertake practical work. All projects will be expected to either investigate or to make use of techniques that are at the leading edge. Project work is a significant element of the MSc and is worth a total of 120 credits (one third of the 360 credit award for the whole programme). All project work is undertaken over the summer months (July/August) on an internship or research placement basis, either with a relevant employer, under a contract research arrangement, or supervised by a member of staff within Queen Mary University of London. The intention of the project component of the programme is that you have the opportunity to apply your knowledge and skills to a real world problem using current state of the art technologies and techniques. At the same time, during the summer, you are also expected to complete the project report, which would normally include a technical document and a non-specialist presentation of your work, and to present your work at a postgraduate research forum which takes place in late September. Projects can range in topic areas; recently completed project examples include:

• Data analysis on traffic flow in London
• Automatic generation of subtitles from video
• Image analysis of handwritten letters
• Predicting customer churn
• Analysing and predicting social media sentiment
• Predicting the risk of readmission in hospital patients
• Analysing data on childhood malnutrition
• Investigating trends in social mobility
• Recommending products to online shoppers
• Predicting the effects of climate change on agriculture
• Forecasting future energy demands
• Fraudulent activity detection
• The use of AI to automatically grade student essays
• Designing a deep learning model to recommend music
• The development of an AI system to manage smart home appliances
• The application of AI techniques in the detection of disease
• Design and development of an AI-powered chatbot
• Sentiment analysis of twitter data
• Using AI techniques in autonomous vehicles
• Applying AI to the problem of cyber-security
• Using natural language processing techniques for automatic summarisation
• Analysing the role of AI in online marketing
• Using AI to understand and predict economic trends
• Understanding and predicting political events through the use of AI.
However, many projects are identified during the course of the year, and it may not be possible to determine the exact topic until you have arrived in London, and commenced your studies.

Course schedule:

The following are the two preparatory modules for the programme:

• Introduction to Scripting and Web Technologies
• Mathematical and Statistical Techniques
Students will also be assigned one of the following 6 compulsory modules in addition to the 2 preparatory modules:
• Risk and Decision-Making for Data Science and AI
• Principles of Machine Learning
• Programming for Artificial Intelligence and Data Science
• Statistics for Artificial Intelligence and Data Science
• Ethics, Regulation and Law in Advanced Digital Information Processing and Decision Making
• Neural Networks and Deep Learning
• Project

Assessment:

Standard modules are assessed through a combination of coursework and written examinations. The project is assessed via a written report, a formal oral presentation and, where applicable, a demonstration of any software and/or hardware you have developed.

Teaching:

The two preparatory intensive modules will be taught through lectures and iterative learning approaches over two weeks, taking place before the start of the academic term. Teaching for all other modules includes a combination of lectures, seminars and use of a virtual learning environment. Each module provides contact time with your lecturers, supported by lab work and self-directed further study. This year, Sky News reported that demand for jobs requiring skills in AI and machine learning is estimated to soar by 40% over the next five years.

Other:

This programme is a Level 7 qualification and is worth a total of 360 credits at QCF Level 7 (180 ECTS credits).

Home: £12,650 Overseas: £29,950