The programme aims to give the students fundamental knowledge and practical skills needed to design, build and apply AI systems in chosen area of specialisation. The wide range of areas in data science and artificial intelligence spans across multiple research disciplines aiming to create skills needed for the digital economy.
Students will develop skills in specialist areas with clear applications in industry, including data mining, pattern recognition and machine learning.
The Master of Science in Data Science and Artificial Intelligence is a 180 credit programme. A student must complete:
- Four core modules (60 credits total)
- Three compulsory modules (45 credits total)
- Three optional modules (45 credits total)
- A final project (30 credits total)
CORE (must pass all assessment elements)
- Artificial Intelligence 15
- Data Programming in Python 15
- Mathematics and Statistics for Data Science 15
- Machine Learning 15
- COMPULSORY (subject to the *rules for compensation)
- Big Data Analysis 15
- Data Science Research Topics 15
- Neural Networks 15
OPTIONAL (choose any four and subject to the *rules for compensation)
- Blockchain Programming 15
- Data Visualisation 15
- Financial Data Modelling 15
- Mathematics for Financial Markets 15
- Natural Language Processing 15
- R for Data Science 15
PROJECT (must pass all assessment elements)
Final Project in Data Science and Artificial Intelligence 30
Rules for Compensation
The university will allow compensation for an assessment element within optional and compulsory modules if:
- the mark awarded for one of the assessment element is between 45%-49%; AND
- the mark for the other assessment elements is sufficient to produce an overall combined weighted pass mark for the module
Note: the university will NOT allow compensation for any assessment element within core modules and the final project.
Entry Route 1
Applicants must have the following:
- A full UK second class honours degree (or its equivalent) in a *relevant subject from an institution acceptable to the University of London; AND
- GCE ‘O’ Level, min Grade C6 in English or its equivalent
The subjects that would be considered as relevant are: Computing, Data Science, Computer Science, Business Computing, Games Programming, Physics, Engineering, Mathematics and statistics, Finance, Marketing and Finance.
Entry Route 2
If applicants do not meet the above academic requirements, their applications may be considered based on the following
- A full UK second class honours degree (or its equivalent) in a any subject from an institution acceptable to the University of London; AND
- GCE ‘O’ Level, min Grade C6 in English or its equivalent; AND
- *Complete and pass an online preparatory course, MOOC via Coursera platform. There is no entry test requirement for the MOOC course. However, there will be assessment during and at the end of the MOOC course
*Students should sign up with Coursera at least 3 months before the intended intake. Do aim to have the results at least one month before the application intake is closed. While completing the MOOC course, student may submit an SIM application.