Machine Learning for Finance - MSc (Online) Programme content
Key information
Key information
- Complete part-time over two years
- Delivered online
- Modules taught during autumn, spring and summer semesters
- Submit dissertation at the end of the summer semester
You will learn through a blend of
- Lectures, workshops, and hands-on activities
- Reflective practice and guided research
- Regular feedback from faculty and peers
Part-time considerations
- Designed for working professionals
- Evening or recorded lectures
- Additional prep and group work time
- Timetable provided after registration
Programme content - Year 1
Core modules
- Introduction to Scientific Computing for AI (CE4021) will introduce you to the relevant programming languages and host platforms for scientific computing.
- Capital Markets and Corporate Finance (FI6161) will develop your knowledge of capital markets and corporate finance, including bond, derivative and foreign exchange markets.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
Core modules
- Data Analytics (CS5062) introduces elements of data analytics workflow, including data clearing, predictive and descriptive modelling, and the deployment of models.
- Derivative Markets (FI6035) will build your awareness and understanding of derivative markets, including how to apply that knowledge to Machine Learning.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
Core modules
- Risk, Ethics, Governance and Artificial Intelligence (IN5013) will highlight the importance of developing AI technologies alongside frameworks informed by risk, ethics and governance.
- Advanced Topics Seminars and Project Specification (CS6163) will begin the process of developing a research and development project, applying AI topics to a tangible business or societal need.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
Programme content - Year 2
Core modules
- Project Management in Practice (MN6041) will explain the role of the project manager, and help you understand how to deal with expectations and build and execute project plans.
- Machine Learning for Finance (FI6024) will offer a practitioner-oriented education in the machine learning algorithms that are used in the capital markets and asset management sectors.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
Core modules
- Deep Learning for Finance (FI6015) will develop your practical skills in deep learning algorithms, including an examination of recurrent neural networks (RNNs) and Long Short Term Memory Networks (LSTMs).
- Artificial Intelligence and Machine Learning (CE6002) will explore how to learn from data, build datasets, and develop algorithms which improve machine learning.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
Core module
- The Project and Dissertation (FI6026) module will see you research, develop, analyse and present a project on an AI or Machine Learning-related problem in finance.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
